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A visual and digital method for predicting discomfort glare
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A visual and digital method for predicting discomfort glare
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A VISUAL AND DIGITAL METHOD FOR PREDICTING DISCOMFORT GLARE by Jonathan Tedjakusuma A Thesis Presented to the FACULTY OF THE SCHOOL OF ARCHITECTURE UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree MASTER OF BUILDING SCIENCE December 2003 Copyright 2003 Jonathan Tedjakusuma Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. UMI Number: 1420403 Copyright 2003 by Tedjakusuma, Jonathan All rights reserved. INFORMATION TO USERS The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleed-through, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. ® UMI UMI Microform 1420403 Copyright 2004 by ProQuest Information and Learning Company. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. ProQuest Information and Learning Company 300 North Zeeb Road P.O. Box 1346 Ann Arbor, Ml 48106-1346 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. UNIVERSITY OF SOUTHERN CALIFORNIA THE GRADUATE SCHOOL UNIVERSITY PARK LOS ANG ELES, CALIFORNIA 90089-1695 This thesis, written by Jgw w A N TemwiwMA under the direction o f h thesis committee, and approved by all its members, has been presented to and accepted by the Director o f Graduate and Professional Programs, in partial fulfillment of the requirements fo r the degree o f IjMtm of sa^ce Date ^ aC T feQ fc -fl Thesis Committee Chair Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ACKNOWLEDGEMENTS My greatest debt of gratitude is owed to God for his grace that allows me to complete this thesis. I would also like to acknowledge the following people who have directly shaped my life and work. Special thanks go to all of my Committee Members: Professor Marc Schiler, Professor Douglas Noble, Professor Ralph Knowles and Professor Murray Milne. I am indebted to all of you due to your importance in my work. Without your gracious support and enthusiasm, it would have been impossible to complete it. My gratitude to all of my friends and classmates for their help in various ways. To Johnny Lu, Gautam R. Shenoy, Xiao Li, Sarada Chidambareswaran, Suganya Thiagarajan, Christine Utomo and many others who have behind the scenes encouraged and supported my work. Finally, I would like to thank my family, especially my parents, for their continual prayers and unrelenting support. I am grateful to have all of you in my life. Thank you very much to each of you and may the glory of God be unto you. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. TABLE OF CONTENTS ACKNOWLEDGEMENTS ............ ii LIST OF TA B LES................ vi LIST OF FIGURES ................................ vii ABSTRACT......................... xiii L THE PROBLEM OF DISCOMFORT GLARE ......... 1 1.1. Introduction to Glare ........ 1 1.2. What is Discomfort Glare? ............................. 2 1.3. Common Methods of Calculating Discomfort Glare are Limited .......... 4 1.4. A Better Visual and Digital Method for Predicting Discomfort Glare is Proposed ........... 6 2. THE ELEMENTS OF DISCOMFORT GLARE .............................. 7 2.1. The Visualization Process .......................................... 7 2.1.1. Physical Aspects ....... 7 2.1.2. Internal Interpretation Aspects ........ 8 2.2. The Nature of Discomfort G lare ............ 9 2.3. Luminance and Illuminance......................... 10 2.4. Contrast .......................... 14 2.5. The Visual Field of View ...................... 15 2.6. Visual Adaptation ......................... 16 2.7. Visual Acuity ................ 16 3. THE ADVANTAGES AND DISADVANTAGES OF THE PAST WORK ON DISCOMFORT GLARE ANALYSIS METHODS ...... 18 3.1. Five Existing Glare Analysis Methods ........................................ 18 3.2. The Subjective Approach of the “British Glare Index” method by R.G. Hopkinson..................... 18 3.3. The Complex Computational Approach of the “Visual Comfort Probability” method by David Dilaura ........... 19 3.4. The Performance Approach of the Relative Visual Performance method byKambich ............ 21 3.5. The High-tech Approach Using Video Photometry by Mark S. Rea ...... 22 3.6. The Quantitative Approach of the Schiler Glare Method by Marc Schiler .............................. 23 iii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 4. THE METHOD AND PLAN OF A PPRO A CH ..... 28 4.1. Selecting the Best Strategies ........ 28 4.2. The Visual and Digital Method for Predicting Discomfort Glare using Both Quantitative and Qualitative Approach 29 4.3. The Components of the Visual and Digital Method ......................... 30 4.3.1. Digital Camera ...... 30 4.3.2. Luminance M eter................. 31 4.3.3. Known Luminance B o x .................... 31 4.3.4. Glare Source ................ 32 4.3.5. The T ask ........... 32 4.3.6. The Setting ............................. 32 4.4. Three Phases of Testing on the Visual and Digital Method ................ 33 4.4.1. Preliminary Testing .................... 34 4.4.2. Quantification Testing.............. 34 4.4.3. Subjective Validation Process................ 34 5. PRELIMINARY TESTING USING THE VISUAL AND DIGITAL METHOD ................ 35 5.1. The Objective of the Preliminary Testing ............... 35 5.2. The Initial T rial ......................... 35 5.2.1. The Initial Trial Analysis .............. 38 5.2.2. Lesson Learned on the Initial T rial ............. 39 5.3. The Glare Source Location T est ............................. 40 5.3.1. The Glare Source Location Analysis .................... 45 5.3.2. Determining the Glare Source Location .................. 46 5.4. The Qualitative Approach Testing........................ 46 5.4.1. The Qualitative Approach Analysis................ 51 5.4.2. Lesson Learned on the Qualitative Approach Testing ............... 52 5.5. Summary of Findings ........ 53 6. QUANTIFICATION TESTING ...... 55 6.1. The Objective of the Quantification Testing ............ 55 6.2. Predicting the Absolute Luminance Level using the Recalibration M ethod ............... 55 6.2.1. The Recalibration Method using the Manual Mode ...... 57 6.2.2. The Recalibration Method using the Automatic Mode .............. 62 6.2.3. The Recalibration Method Analysis .................................... 67 6.3. Analyzing the Behavior Change in the Histogram .................... 67 6.3.1. Analysis using Adobe Photoshop ........... 68 6.3.2. Analysis using Culplite ............. 72 6.3.3. The Median Vs The Mean of the Background Luminance ..... 78 6.4. Summary of the Quantification Testing........................... 79 iv Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 7. SUBJECTIVE VALIDATION PROCESS ...................................... 81 7.1. The Objective of the Subjective Validation Process ......................... 81 7.2. The Validation Process of the Schiler Glare Method ........................ 81 7.3. The Result and Analysis of the Validation Process .......................... 84 7.4. Potential Flaws of the Approach 102 7.4.1. Small Sample Size ........................................................ 102 7.4.2. Researcher Participation ................................................. 102 7.4.3. Demographics ................................................. 102 7.5. Summary of the Subjective Validation Process ......................... 103 8. CONCLUSION .................................... 104 9. FURTHER STU D IES.......................................................... 107 10.REFERENCES ............................. 109 APPENDICES Appendix A: Review of Research Involving Human Subject Approval Notice ... I l l Appendix B: Consent to Participate in Research ..................................... 112 Appendix C: The Validation Survey Forms ...................... 121 Appendix D: The GR-DVL725U Specification ........................................ 130 Appendix E: The Luminance Meter Specification ..................................... 132 Appendix F: Claim of Exemption 133 v Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. LIST OF TABLES Table 5.1: The degree of visual discomfort comparison between the first and second exeriments ....... 45 Table 6.1: The comparison between the absolute value and the pixel value of the digital image (Digital images were recorded using the manual m ode) ............ 60 Table 6.2: The comparison between the absolute value and the pixel value of the digital image (Digital images were recorded using the automatic m ode) ................... 64 Table 7.1: The validation survey result ............. 84 Table 7.2: The list of figure numbers in relation to the setting numbers ............ 87 Table 7.3: The comparison table between the qualitative and the Schiler quantitative glare theory............................ 97 vi Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. LIST OF FIGURES Figure LI: Low angle afternoon sunlight penetrates a window opening and may cause discomfort glare................... 3 Figure 1.2: An exposed artificial lighting fixture may cause discomfort glare towards the occupants in some particular cases ........................ 3 Figure 1.3: Sample of veiling reflection ................ 3 Figure 1.4: Angle of reflection 3 Figure 1.5: Avoiding veiling reflection ........ 3 Figure 2.1: The Eye Anatomy .................. 8 Figure 2.2: A game of human visual perception I ...... 9 Figure 2.3: A game of human visual perception I I .......................... 9 Figure 2.4: Sketch of discomfort glare process .............. 10 Figure 2.5: Luminance is the amount of light leaving a projected surface 11 Figure 2.6: Illuminance is the amount of light that energy arrives at a surface .... 11 Figure 2.7: An example of a desk lamp with a translucent shade................ 13 Figure 2.8: High luminance contrast may lead to the occurrence of discomfort glare.............. 15 Figure 2.9: Human Visual Field of View .............. 15 Figure 2.10: Visual acuity example ......................... 16 Figure 2.11: Which font size do you prefer least? ........ 17 Figure 3.1 : The known luminance b o x ........ 24 Figure 3.2 : The earlier measurement.................................................... 24 Figure 3.3 : The measurement taken a year later ...................... 24 Figure 3.4 : Example of digital image ............... 25 vii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 3.5 : Sample of histogram taken from the digitized image ........ 26 Figure 3.6 : The shape of a bell curve in the histogram .............................. 26 Figure 4.1 : The JVC GR-DVL725U ......... 30 Figure 4.2 : The Luminance Meter ...... 30 Figure 4.3 : The Known Luminance B o x.............................. 31 Figure 4.4 : The glare source recorded on difference luminance level ............. 32 Figure 4.5 : The experiment setting ........ 33 Figure 5.1 : The setting for the first trial experiment............... 35 Figure 5.2 : The comfort rating felt on the 6 different luminance levels 36 Figure 5.3 : The histogram taken from the 6 different luminance levels ........... 37 Figure 5.4 : The image and histogram taken from the 4th condition luminance level ............... 38 Figure 5.5 : The known luminance box should be placed away from the observer’s field of view ...................................... 39 Figure 5.6 : On the second setting, the location of the glare source was moved further to the le ft ........ 40 Figure 5.7 : The image taken from the first and second settings with their visual discomfort ratings .............. 41 Figure 5.8 : The histogram taken from the first and second settings.................... 43 Figure 5.9 : The setting for the third trial experiment................................. 47 Figure5.10: 1stCONDITION ......... 47 Figure 5.11: 2ndCONDITION ............................... 48 Figure 5.12: 3rdCONDITION ......... 48 Figure 5.13: 4th CONDITION ............... 49 Figure 5.14: 5th CONDITION ...... 49 viii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 5.15: 6thCONDITION ............................................................. 50 Figure 5.16: 7thCONDITION ............................................................. 50 Figure 5.17: A sample image taken from the 3rd condition of the third trial ........ 51 Figure 5.18: A sample histogram taken from the 3rd condition of the third trial... 51 Figure 5.19: The Final Setting .................. 53 Figure 5.20: The observer’s field of view ...... 53 Figure 6.1 : The Recalibration Setting .................................................. 56 Figure 6.2 : The glare source at 0 foot-Lambert (Manual m ode) 57 Figure 6.3 : The glare source at 10 foot-Lambert (Manual mode) .................. 57 Figure 6.4 : The glare source at 20 foot-Lambert (Manual m ode).................. 58 Figure 6.5 : The glare source at 30 foot-Lambert (Manual m ode) ....... 58 Figure 6.6 : The glare source at 40 foot-Lambert (Manual m ode).................. 58 Figure 6.7 : The glare source at 50 foot-Lambert (Manual m ode).................. 58 Figure 6.8 : The glare source at 60 foot-Lambert (Manual m ode) 58 Figure 6.9 : The glare source at 70 foot-Lambert (Manual m ode).................. 58 Figure 6.10: The glare source at 80 foot-Lambert (Manual m ode) ................ 59 Figure 6.11: The Adobe Photoshop color sample tool ................................. 59 Figure 6.12: The non-linearity relation between the pixel value and absolute luminance level of the glare source ....................................... 60 Figure 6.13: The glare source at 0 foot-Lambert (Automatic m ode)................ 62 Figure 6.14: The glare source at 10 foot-Lambert (Automatic m ode)............... 62 Figure 6.15: The glare source at 20 foot-Lambert (Automatic mode) . 62 Figure 6.16: The glare source at 30 foot-Lambert (Automatic mode) ............... 62 ix Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 6.17: The glare source at 40 foot-Lambert (Automatic m ode)............... 63 Figure 6.18: The glare source at 50 foot-Lambert (Automatic m ode) ......... 63 Figure 6.19: The glare source at 60 foot-Lambert (Automatic m ode)............. . 63 Figure 6.20: The glare source at 70 foot-Lambert (Automatic m ode) ...... 63 Figure 6.21: The glare source at 80 foot-Lambert (Automatic m ode)............... 63 Figure 6.22: The relationship among the absolute luminance values, the glare source pixel values, and the known luminance pixel values (Digital images were recorded using the automatic mode) ...... 64 Figure 6.23: The center-weighted average measurement system 65 Figure 6.24: The spot measurement system ............... 66 Figure 6.25: An image sample and its histogram..................... . 67 Figure 6.26: The 10 FL desk lam p.................... 68 Figure 6.27: The 20 FL desk lamp .............. 68 Figure 6.28: The 30 FL desk lamp ........ 68 Figure 6.29: The 40 FL desk lamp ............................. 68 Figure 6.30: The 50 FL desk lamp ....... 69 Figure 6.31: The histogram of the 10 FL desk lamp .................... 69 Figure 6.32: The histogram of the 20 FL desk lamp ................................... 69 Figure 6.33: The histogram of the 30 FL desk lamp .............. 70 Figure 6.34: The histogram of the 40 FL desk lamp ......... 70 Figure 6.35: The histogram of the 50 FL desk lamp ................................... 70 Figure 6.36: The double layered histogram of the 10 FL desk lamp ..... 71 Figure 6.37: The double layered histogram of the 20 FL desk lamp ......... 71 x Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 6.38: The double layered histogram of the 30 FL desk lamp ........... 71 Figure 6.39: The double layered histogram of the 40 FL desk lamp ................ 71 Figure 6.40: The double layered histogram of the 50 FL desk lamp ............. 72 Figure 6.41: The sample image built from the .RAW file ............................. 73 Figure 6.42: output from Culplite .......................................................... 74 Figure 6.43: The culplite analysis method on second setting (20 FL desk lam p).. 76 Figure 6.44: The culplite analysis method on the third setting (30 FL desk lamp) 77 Figure 7.1 : First Setting (Desk lamp luminance = 4.87 foot-Lambert) ............ 82 Figure 7.2 : Second Setting (Desk lamp luminance = 9.8 foot-Lambert)............. 82 Figure 7.3 : Third Setting (Desk lamp luminance = 14.8 foot-Lambert)............ 83 Figure 7.4 : Fourth Setting (Desk lamp luminance = 25.1 foot-Lambert) .......... 83 Figure 7.5 : Fifth Setting (Desk lamp luminance = 40.1 foot-Lambert).............. 83 Figure 7.6 : Sixth Setting (Desk lamp luminance = 75 foot-Lambert) .............. 83 Figure 7.7 : Seventh Setting (Desk lamp luminance = 106 foot-Lambert) ......... 83 Figure 7.8 : Eight Setting (Desk lamp luminance = 152 foot-Lambert) .......... 83 Figure 7.9 : Ninth Setting (Desk lamp luminance = 175 foot-Lambert) ............ 83 Figure 7.10: The validation survey result chart ....... 85 Figure 7.11: Setting the visual field of view ............ 86 Figure 7.12: The first setting (desk lamp luminance = 4.87 foot-Lamberts) 88 Figure 7.13: The second setting (desk lamp luminance = 9.8 foot-Lamberts)...... 89 Figure 7.14: The third setting (desk lamp luminance = 14.8 foot-Lamberts) ...... 90 Figure 7.15: The fourth setting (desk lamp luminance = 25.1 foot-Lamberts) 91 Figure 7.16: The fifth setting (desk lamp luminance = 40.1 foot-Lamberts) ....... 92 xi Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 7.17: The sixth setting (desk lamp luminance = 75 foot-Lamberts) ......... 93 Figure 7.18: The seventh setting (desk lamp luminance = 106 foot-Lamberts).... 94 Figure 7.19: The eight setting (desklamp luminance = 152 foot-Lamberts)....... 95 Figure 7.20: The ninth setting (desklamp luminance =175 foot-Lamberts)....... 96 Figure 7.21: The glare source from the second setting was taken from the background .................. 98 Figure 7.22: The glare source was placed on different layer ................ 98 Figure 7.23: The original histogram of the second setting with both background and glare source together ........ 99 Figure 7.24: The histogram of only the glare source within the image ...... 99 Figure 7.25: The image taken from the second setting (without the glare source) 99 Figure 7.26: The histogram generated from figure 7.25 ....................... 100 Figure 7.27: First Setting (The number of spike pixels compared with the background pixels) .............. 101 Figure 7.28: Second Setting (The number of spike pixels compared with the background pixels) ............................. 101 xii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ABSTRACT This thesis develops a visual and digitized method for predicting the occurrence of discomfort glare, which involves both quantitative and qualitative approaches as its validation process. The quantification approach uses the histogram of pixel luminosity of a digital image for predicting discomfort glare. The qualitative approach validates the quantification approach using human test subjects to ascertain the prediction results. The method involves a common and affordable technology to provide a more useful and accurate solution for architects in avoiding discomfort glare in their design. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER I THE PROBLEM OF DISCOMFORT GLARE 1.1 INTRODUCTION TO GLARE Glare is a common problem in the architectural and lighting design fields. For centuries, many architects, interior designers and lighting designers have had troubles with this qualitative design issue. The occurrence of glare in a space reduces the occupant’s productivity and deteriorates their mood. In other words, it has many negative effects on the physiology and psychological aspects of the occupant in a given space. With good architectural design, architects should be able to control glare and add more qualitative values for the occupants and their surroundings. Since the beginning of the twentieth century, scientists have conducted research and experiments to find methods to counteract glare. In the past 90 years, the study of glare has rapidly expanded and produced promising results, but the complete nature of glare has not yet been fully defined. Among all of those attempts, some methods required tedious mathematical calculations and expensive high-tech equipment. I believe a more practical approach using current low-tech equipment can be used to analyze the occurrence of glare, in particular discomfort glare. There should be a 1 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. visual and digital method that can he used by architects, interior designers, and lighting designers worldwide to predict discomfort glare in the early stages of the design phase. 1.2 WHAT IS DISCOMFORT GLARE? Glare, basically, is an unwanted light. It happens when our eyes have adjusted to a certain general brightness, then suddenly some annoying, distracting, and sometim es blinding light strikes our visual field of view. It has generally been divided into two broad categories: discomfort glare and veiling reflection. Discomfort glare occurs when our eyes are impacted by an excessively bright light in relation to the general brightness level. This is the most common form of glare that occurs in architecture design. Designing window openings facing towards direct afternoon sunlight is one of the clearest examples of discomfort glare (figure 1.1). It is essential to provide shielding to avoid the penetration of direct light and to control brightness and contrast inside the space. Another example occurs with artificial lighting for building interiors. A poorly designed exposed light fixture in a building interior may cause discomfort glare to the occupant of the space. Instead of setting up a mood for the occupants, it causes strain and pain in their eyes. Thus, it reduces their productivity and health (older people tend to be more sensitive in this matter). Discomfort glare can be present in any degree of brightness without a loss in ability to see, but when it exists to an excessive degree that might reduce the ability to see and cause temporary blindness, it is called disability glare. 2 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 1.1: Low angle afternoon sunlight penetrates a window opening and may cause discomfort glare. (Gordon & Nuckolls, 1995, p. 21) Figure 1.2: An exposed artificial lighting fixture may cause discomfort glare towards the occupants in some particular cases. (Hopkinson, 1963, cover page) A veiling reflection is a reflected light that veils or masks some of the information we see. This type of glare often happens when we read a magazine and some part of the page is veiled or masked by the reflection of light that comes to our eyes (figure 1.4). This type of glare can be avoided easily by changing the angle of incidence or the light fixture placement. Missing Information * * '1 > ? lijtA / ! D Figure 1.3: Sample of veiling reflection. (Cover of Architectural Lighting, 1983) Figure 1.4: Angle of reflection. (Egan & Glgyay, 1983, p.28) Figure 1.5: Avoiding veiling reflection. (Egan & Qlgyay, 1983, p.28) 3 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 1.4 and figure 1.5 show two different lamp placements, which also explain that the lamp on figure 1.4 causes a veiling reflection if the angle of reflection is directly aiming towards the occupant’s eyes. This problem can be avoided by simply tilting or moving the book around to change the angle of reflection. A good architectural design solution is shown in figure 1.5 where the lamp is placed on the side and above the occupant’s eyes where the veiling reflection can be avoided. Discomfort glare is the primary focus of this research. Predicting the occurrence of discomfort glare is more critical in architectural design practices than the prediction of veiling reflections. Moreover, by having controls over the occurrence of discomfort glare, we are able to eliminate it and most likely veiling reflection too. 1.3 COMMON METHODS OF CALCULATING DISCOMFORT GLARE ARE LIMITED Contrast is the difference between dark and light. Discomfort glare is also a result of light and contrast. It was originally believed that discomfort glare could be avoided using a set of rules of thumb. It was thought that the contrast ratio of brightness (between glare and its surrounding) should be 3 to 1. When contrast increases to a ratio of 10 to 1, discomfort glare occurs and starts to become problematic. In reality, others argue that this ratio is clearly not true and too simplistic in explaining the phenomenon of discomfort glare. For instance, if we have a printed black type on a white paper, the brightness contrast ratio is over 50:1. However, we do not experience discomfort glare. 4 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Most existing glare research is based on consideration of size, luminance (brightness), the number of glare sources, and the background luminance (brightness). Researchers also have already come up with the measurement of VCP (Visual Comfort Probability), which is based on empirical relations derived from a variety of experiments (Dilaura, 1976, M y). The downside is that this research cannot be applied to any different conditions, except specific conditions identical to the test. Hence, it is clearly not enough to define discomfort glare in general conditions. None of the above methods used the current visual and digital technology to capture the entire field of view of human eyes, which is really useful in measuring and analyzing the data about discomfort glare. There have been more recent attempts to apply video photometry to capture the image and determine the luminance level and possible glare (Rea, 1986). Nonetheless, they focused on the use of expensive equipment and calibrated their cameras to obtain absolute values instead of analyzing the problem. Human eyes are far beyond the most recent and advanced technology. Based on the research by Schiler (2000), “Toward a Definition of Glare: Can Qualitative Issues Be Quantified?” we are able to use the video digital method to measure and compute the tedious calculation in a really short time. However, we still cannot be certain that the method definitely does predict the occurrence of discomfort glare based on the numerical data alone. It needs both qualitative and quantitative approaches to demonstrate that the method really works. The data needs to be subjectively verified by a number of observers as part of the validation process. 5 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 1.4 A BETTER VISUAL AND DIGITAL METHOD FOR PREDICTING DISCOMFORT GLARE IS PROPOSED Hypothesis: “A better visual and digital method using both qualitative and quantitative approaches will provide a more generally useful measure o f discomfort glare in Architectural design.” There are four premises to this hypothesis. The first premise is that discomfort glare is a serious issue in architecture that is not yet fully defined. Second, the common methods of calculating discomfort glare are impractical. Thirdly, a visual and digital method of predicting glare is more effective since it does not require tedious manual calculations. Finally, the current visual and digital discomfort glare prediction method needs to be validated using both qualitative and quantitative approaches. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER II THE ELEMENTS OF DISCOMFORT GLARE 2.1 THE VISUALIZATION PROCESS Our vision or ability to see is the process of how our brain perceives information through our eyes, which is also called visual perception. There are two aspects that compose our visual perception: 1. Biophysical Aspects (our eye and its function). 2. Internal Interpretation Aspects (how our mind processes the data). 2.1.1 BIOPHYSICAL ASPECTS Our eyes are an incredible visual tool. They are a primary sense to gather information from the outside world. The whole process starts from the cornea and lens that receive and focus light from the outside world onto the retina, which transmits the impulse to the brain through the optic nerve. Under different brightness conditions, the iris controls the size of the pupil and admits the optimum amount of light into the eye. The iris reduces the size of the pupil when it is bright and vice versa. The ability of the eye to control the amount of light coming into the retina is called adaptation. 7 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. / t C ornea # * Optic Neive Figure 2.1: The Eye Anatomy (Egan & Olgyay, 1983, p.36) The retina consists of light sensitive rods and cones. Rods are highly sensitive to motion and bright light. They function only in dim and low levels of light. On the other hand, cones function in bright light, perceiving colors and detail. Color or cone- based vision is called photopic vision, and monochromatic or rod-based vision is called scotopic vision. 2.1.2 INTERNAL INTERPRETATION ASPECTS When our brain receives information from the optic nerve, it processes the data and enables recognition and understanding. Experiences, expectations and emotions influence the perception or evaluation of our visual images. Here are some examples of how our expectations do influence and can be easily twisted to give us confusing perception. 8 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. is the left center circle bigger? No, they're both the same size Figure 2.2: A game of human yisual perception I (http://www.angelfire.com/retro/wyandanch/optical/page_01.htm). ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ Are the horizontal lines parallel or do they slope? Figure 2.3: A game of human visual perception II (http://www.angelfire.com/retro/wyandanch/optical/page_01.htm). 2.2 THE NATURE OF DISCOMFORT GLARE The nature of discomfort glare first occurs when our eyes are adapted to an overall low light level, which also means that our iris aperture is wide open to accommodate more light coming into our eyes. If there is one point light source whose brightness is substantially greater than the overall brightness within the human visual field of view, that one light point source will effectively “bum a hole” at the retina where it is focused. This will create visual discomfort to our eyes (figure 2.4). 9 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Cornea Figure 2.4: Sketch of discomfort glare process As a result, we will make an adjustment by squinting and turning away, trying to correct the environment. Another adjustment is to control the contrast ratio, such as decreasing the brightness of the glare source or increasing the overall brightness level. Being exposed to discomfort glare for some period of time can reduce our performance or productivity. We will have a hard time concentrating and will easily get tired in doing our task. In some extreme cases, discomfort glare might cause damage to our physical and psychological aspects. For example, older people have less ability than younger people to adapt with those extreme changes. When we are aging, our visual flexibility or adaptation decreases. 2.3 LUMINANCE AND ILLUMINANCE Luminance is one of many important aspects in discomfort glare, which is often misunderstood with the concept of illuminance. Luminance is the amount of light 10 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. leaving a projected surface, whereas illuminance is the amount of light energy that ■ arrives at a surface. Luminance Figure 2.5: Luminance is the amount of light leaving a projected surface. M uminance Figure 2.6: Illuminance is the amount of light that energy arrives at a surface. Illuminance is a measure of how much light energy (luminous flux) is intercepted by a surface. It is best defined by using the formula below: E = dO/dA or E = F/A where: where: <p = dQ/dt E = illuminance Q = radiant energy (visible spectrum) F = light energy (luminous flux) t = time A = the receiving surfaces area A = the receiving surfaces area The English system unit of measure for illuminance is the foot-candle (fc) or lumen per square foot, while in the SI system the unit is the lux (Ix). As a comparison, the value of one foot-candle is equal to 10.764 lux. 11 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Unlike illuminance, luminance is a measure of how much light energy (luminous flux) is leaving a projected surface. There are several measurements in defining luminance. Initially, the measure of how much light energy leaving a surface is defined by the term exitance (M), which is the total luminous flux leaving a surface. The unit of measure for exitance is the lumen per square foot. M = dd>/dA ( where: €> = dQ /dt Q = radiant energy (visible) t = time A = the projected surface area M = F/A where: M = exitance F = the light energy (luminous flux) leaving the projected surface A = the projected surface area Exitance is best used for determining the total luminous flux leaving a matte surface, which diffuses or scatters the light energy. However, exitance does not calculate the direction of where the light energy comes and leaves from the projected surface. In other words, it does not work well on a specular surface. Another measure is luminance, which is the total luminous flux density leaving a surface in a particular direction. It is a measurement of how bright the surface looks. 12 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Luminance includes the direction factor of the light energy, which is described by the formula: L = d2 n / do dA© Where L = luminance A© = the area viewed from angle 0 C O = the solid angle (steradians) The unit of measure for luminance is the foot-Lambert (£L) in the English system, which is equal to one lumen per square foot. In comparison with the SI system, one foot-Lambert is equal to 0.2919 Candela per square meter (Schiler, 1992, pp. 14-15). Figure 2.7: An example of a desk lamp with a translucent shade. Another way of defining luminance is using the old convention where luminance is the function of illuminance multiplied by the surface reflectivity or transmissivity. The luminance of a surface refers to the amount of light being reflected or transmitted 13 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. through the surface. For instance, the luminance of a white paper is related to the surface reflectivity of the white paper surface and the amount of light falling onto it. In another case, when we refer to a translucent material such as the shade of a desk lamp (Figure 2.6), the surface transmissivity of the shade controls how much light is being transmitted. In other words, a simple way of explaining the relationship among the luminance, illuminance, surface reflectance and surface transmittance is described as follows. L = Luminance E = Illuminance p = the surface reflectance x = the transmittance 2.4 CONTRAST Our visual perception of the outside environment is based on the quantity of contrast (the difference between light and dark). Contrast is needed to view an object and to sense the luminance of surfaces. The magnitude of contrast in a space influences the mood and affects our productivity. For example, it is easier to read an article on a piece of white paper with black text instead of grey. Luminance contrast can be calculated by comparing the luminance value or the reflectance value of the surface. For instance, if the black text reflectance value is 5%, the grey text is 40%, and the white paper is 80%, the luminance contrast is calculated by comparing the black text reflectance value over the paper reflectance (5:80) with the gray text reflectance over the paper reflectance (40:80). The result is that higher contrast helps us gaining better visual perception. 14 L = ExporL~ExT Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. However, glare may also occur because too much contrast is involved. When we are reading a book inside a relatively dim room with the overall luminance level of 3 foot- Lambert, our eyes are adapted to the overall dim space. However, if a desk lamp is located right in front of us with the luminance level of 100 foot-Lambert, there is a high luminance contrast and most likely, discomfort, glare occurs (figure 2.8). Figure 2.8: High luminance contrast may lead to the occurrence of discomfort glare (Hopkinson, 1963, p.23). 2 3 THE VISUAL FIELD OF VIEW Eyebrow (shields e^e-frem overhead glare) Fovea I vision------------------ Cutoff of vision btj aifebreu)— V iew bt| b o th ey es* ^ (binesular vision) Line af sight Visual surround of fovea I vision (beuona 30! vision is indistinct) V iew bij left e^e alone (monocular vision') Cutoff of vision b u g cheek and nose Figure 2.9: Human Visual Field of View (Egan & Olgyay, 1983, p.40). 15 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. The visual field of view is the visual plane within the visual angle of our eyes. Our visual field of view can extend to 130° vertically and more than 120° horizontally when both eyes are focused on a fixed object; this is also called the binocular visual field. 2.6 VISUAL ADAPTATION Visual adaptation is the ability to accommodate different illuminance ranges. Our eyes have an amazing range of adaptation, which allows them to adjust from below 1 fc to over 10,000 fc in moments. Our eyes need some time to adapt each time there is a change in overall luminance; this is called the time of adaptation. Our visual adaptation will become problematic if the change in luminance is too rapid or when there is one really bright spot of light while the overall background luminance is dark (both can be disability or discomfort glare). 2.7 VISUAL ACUITY Visual acuity is the sharpness of detail that we are able to see at a given distance. When we compare these two phrases below, figure 2.9 results in better visual acuity than figure 2.10 because of the difference in contrast ratios. VISUAL ACUITY i I Figure 2.10: Visual acuity example 1 6 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Visual acuity is determined by the time of adaptation, contrast and luminance. In figure 2.10, our eyes need more time to adapt and read it. Another example is shown in figure 2.11 that our visual acuity increases as the font size increases. visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity visual acuity Figure 2.11: Which font size do you like least? 1 7 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER III THE ADVANTAGES AND DISADVANTAGES OF THE PAST WORK ON DISCOMFORT GLARE ANALYSIS METHODS 3.1 FIVE EXISTING GLARE ANALYSIS METHODS Much research has been conducted to find a good glare analysis method. There are five significant glare analyses methods. Those five glare analyses are: 1. The British Glare Index Method 2. The Visual Comfort Probability Method 3. The Relative Performance Method 4. The Video Photometry Method 5. The Schiler Glare Method Each method has a different approach, which is fundamental for this research. Thus, it is important to know their advantages and disadvantages as described below. 3.2 THE SUBJECTIVE APPROACH OF THE “BRITISH GLARE INDEX” METHOD BY R.G. HOPKINSON The British Glare Index approach was first introduced by R.G. Hopkinson (1963). Using a subjective testing approach, he discovered a relationship among the background luminance, the luminance of the possible glare sources, and the field of 18 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. view when glare occurs. In Ms experiments, he calculated the summation of the multiple glare sources by simply adding the glare sensation value. T 1.6 0.8 Ls x c o G total = 2 1 Lb X p Then he converts it to his Glare Index System by taking it 10 times the logarithm of the sum (Gtotai) G ln o p k in s o n — 10 lOglO G jo ta l To set the limit where glare first occurs, he asked a number of observers whether the degrees of glare set were acceptable to them. Based on the survey, he related the result with the calculated values and validated his theory qualitatively. His theory concludes that the bigger differences between the background and possible glare level, the more glare index will increase. The wider field of view would decrease the glare index. Many researchers had been fascinated by his theory and had conducted further studies using his methods and principals to define discomfort glare. 3.3 THE COMPLEX COMPUTATIONAL APPROACH OF THE “VISUAL COMFORT PROBABILITY” METHOD BY DAVID DILAURA Visual Comfort Probability is the discomfort glare evaluation rating, which was originally developed by S.K. Guth (1966), and later completed by David L. Dilaura 19 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. (1976). It has been used for decades by the IESNA (Illuminating Engineering Society of North America) to evaluate discomfort glare. Basically, it is the estimated percentage of how people feel discomfort glare in a given situation. The experiment involves a tedious calculation method, which takes fluorescent lights with various diffuser types as the glare source. It calculates the light source location, luminance level, viewed angles, and the surface brightness. Where DGR= Discomfort Glare Rating L = luminanire luminance Q = solid angle factor P = position index Lbs = background luminance Then the DGR is converted to VCP value (range from 1 to 100 value) by using the following formula. n -0.0914 LQ DGR= E 6.374-1.32271n(DGR) VCP = (271)0.5 100 e-t2 /2 dt 2 0 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Generally, the recommendation rating for offices and schools should have a VCP of 70. For a room with VDTs (Visual Display Terminals), it is recommended to have a VCP of 80. A similar concept and approach is the UGR (Unified Glare Rating) system, which is more world-widely used. UGR uses similar variables to VCP, but differs in the weighting assigned to each parameter; it is shown in the formula below. UGR = 8 log Where 0.25 L8 2 g > E — — Lb p2 UGR= Unified Glare Rating Lb = average background luminance Lg = luminanire luminance to = solid angle of the luminaire P = position index Both methods involve tedious calculations and work only with the given luminaires and conditions. Thus, they are not good approaches to evaluate general discomfort glare in architectural design practice. 3.4 THE PERFORMANCE APPROACH OF THE RELATIVE VISUAL PERFORMANCE METHOD BY KAMBICH Relative Visual Performance is the measure of human visual performance with regards to discomfort glare. This study was made based on the speed and accuracy of performing a task. A number of people were asked to perform a task in a given room lit by a particular light source. While the background and the light source illuminance 21 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. level were changed, the time taken by the occupants to finish the task and the number of errors being performed were recorded. This method is best used for measuring the productivity of a result of the changing illuminance on a surface, but is not useful for evaluating the luminance quality of discomfort glare in a space (Kambich, 1991). 3.5 THE HIGH-TECH APPROACH USING VIDEO PHOTOMETRY BY MARK S. REA Mark S. Rea (1986) developed an image analysis system to measure the luminance level using video photometry systems. The system involves a high technology video camera with a photopic correction filter to capture calibrated images of a scene. Subsequently, the calibrated image is analyzed using image analysis software that is capable of predicting the actual luminance level from the image of the scene. To verify the linear relationship between the actual luminance value and the acquired data in the image, Rea uses a calibrated luminance photometer to compare them. Although he obtained a linear response on his experiment, the non-linearity may still appear due to the sensitivity and accuracy of the equipment or even the temperature of the testing condition. According to Rea, the potential problem can be minimized by repeatedly recalibrating the camera or by stabilizing the camera temperature. Rea has shown an interesting example in the application of video photometry in determining the luminance level in architecture and lighting design fields. His method can also be used in predicting the occurrence of visual discomfort due to discomfort 22 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. glare. However, the downside of this method is that it requires expensive equipment and relies too heavily on equipment recalibrations. 3.6 THE QUANTITATIVE APPROACH OF THE SCHILER GLARE METHOD BY MARC SCHILER Most of the methods described earlier do not capture the entire human field of view. However, Schiler developed a strategy to predict possible glare within the entire human field of view. His method uses an inexpensive and non-calibrated video camera, a known luminance light source placed within the field of view and common software such as Microsoft Excel and Adobe Photoshop to sort and analyze the results that create glare (Schiler, 2000). One of the unique tools used is the k n o w n luminance box. A fluorescent light tube and its ballast are placed inside a reflective box with a high-density opal glass diffuser. There is also an absorptive cavity lined with black felt. The lit panel provides a known luminance of approximately 200 foot-Lamberts (lumens/ft2). The absorptive cavity provides a surface of approximately 0 foot-Lambert. The range of differences between 0 to 200 foot-Lamberts will be picked up by the camera, which is used as the ratio of the known absolute values. Afterward, the luminance value of the other portion of the image in the entire field of view can be determined by finding the relationship between the particular luminance value and the known absolute value. 23 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 17.5 inches X 7 15.75 in J 8 ins 18 in luminous panel / Figure 3.1: The known luminance box. The known luminance box was placed under the desk against the window outside the occupant field of view to avoid any disturbance to the visual adaptation of the occupant. The occupant was given a task to fill out a questionnaire about the visual comfort of the space. The purpose of the questionnaire was only for guidance in interpreting the occupant’s behaviors. A camera was mounted facing the outside wall to capture the whole image, including the luminance of the window, position of blinds, solar position, sunpatch and shadows between the rooms. 98.5 184 SS.0 97.6 209 09.0 Figure 3.2: The earlier measurement. Figure 3.3: The measurement taken a year later. 2 4 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. A luminance meter was used to measure the known luminance surfaces under several conditions. The measurement was taken twice within a one-year range to determine the lumen depreciation and possible dirt depreciation caused by time. Here is the result of the luminance distribution. The sorted image with glare was digitized, and then it was plotted to a histogram. The histogram displayed the frequency of occurrence of each pixel with different intensities within the image. The histograms were used to analyze the distributions, which could be consistently associated with discomfort glare. The following shows an example of the image and the histogram. Figure 3,4: Example of digital image. 2 5 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Wstegjraitt of taitissaie* Ottlflbiitlon m m - r -.— _ _ _ — _ _ _ _ _ _ _ -------------------------- — A ias» i i f M I 10830 J P sm % « § i i? a m si- #1 »? m m m m W *»i% a fS M k e l Figure 3.5: Sample of histogram taken from the digital image. It was found that a shape of a bell curve occurred in almost all of the histograms tested. The bell curve appears to be a representative of the background level. Wstogfsei of Luitftnanc* OisHtoatian S X BELL CURVE 10003 I i i i? 3 3 « m « s? m m sssmi Figure 3.6: The shape of a bell curve in the histogram. A wider bell curve implies a more uniform distribution of light intensities. The ratio of intensities is represented by the X axis (0 to 255 values), ranging from dark to bright; while the Y axis represents the number of pixels at the given intensity. The luminance contrast ratio between the glare source and the background can be analyzed from the histograms and is used to predict the occurrence of discomfort glare. The position of the “spike” on the histogram (figure 3.6) to the bell curve determines the visual 26 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. comfort within the space. The further the position of the spike from the bell curve, the contrast of the luminance intensities increases and this could be a potential glare. The histograms are numerically analyzed in terms of the median pixel intensity, number of background pixels, maximum intensity and ratio between the maximum intensity and the background level. Based on the analysis, the histogram that only has a spike located to the left of the bell curve does not represent glare. Most of the situations with a spike to the right do cause glare. This means that the absence of glare can be predicted. On the contrary, the presence of glare is not yet reliably predicted. The position of the camera is also critical to this method. These observations have been made with the entire field of view. But there are other locations that were also interesting to be tested, such as the observer’s field of view, which faced towards the table with the questionnaire on it. The contrast ratio between the maximum and minimum intensities could exceed 1:200 without creating glare. However, the ratio between the extreme luminance intensities and the median o f the background luminance intensities are more crucial in determining glare conditions. From the result, Schiler concluded that starting from the ratio 2:1 (glare to median background), it began to feel uncomfortable; ratios 3:1 or greater produce a sensation of discomfort and should be avoided. 27 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER IV THE METHOD AND PLAN OF APPROACH 4.1 SELECTING THE BEST STRATEGY Finding the right method for predicting the occurrence of discomfort glare involves both qualitative and quantitative aspects. Discomfort glare is a qualitative issue, which has influence on human visual performance. However, using the qualitative approach alone does not allow computation and prediction of glare situations. Conversely, using the quantitative approach alone without validation could result in biased conclusions. The qualitative approach involves a human as the subject who determines whether a condition is a discomfort glare. The quantitative approach involves numerical analyses which are also necessary for setting up standards or design guidelines and for calculating and predicting the occurrence of discomfort glare. Correlating the qualitative and the quantitative could provide validation for the quantitative. Hopkinson, Guth and Dilaura did run their experiments using both approaches. The downside of their approaches is that they involve a tedious calculation or are only 28 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. applicable to a certain condition. On the other hand, the new approach uses the visual digital technology to evaluate discomfort glare quantitatively. The Schiler glare method is more practical and more applicable to various conditions. Nonetheless, the experiment itself has not been validated yet by using the qualitative approaches. My method is basically a further study based on the Schiler glare method by using both qualitative and quantitative approaches. 4.2 THE VISUAL AND DIGITAL METHOD FOR PREDICTING DISCOMFORT GLARE USING BOTH QUANTITATIVE AND QUALITATIVE APPROACH The idea is to study a visual and digitized method for predicting the occurrence of discomfort glare using both qualitative and quantitative approaches. On the qualitative approach, I asked a number of students (age range 18-28) to perform a task in a room with a light source directly aimed at them and located within their field of view. Subsequently, I asked them, each time I changed the luminance level of the light source, whether or not they feel visually comfortable in the given space. On the quantitative approach, I recorded all of the changes within their field of view using a digital camera. Afterward, using the current image analysis software (such as Adobe Photoshop, etc), I converted the digital image to histogram and ran a quantitative analysis on the histogram to evaluate the predicted occurrence of discomfort glare. Finally, the qualitative survey results were used to validate the quantitative analysis approaches. 29 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 4 3 THE COMPONENTS OF THE VISUAL AND DIGITAL METHOD The method requires a number of components. Each component has its role as a variable. One of the goals in this experiment is evaluating each variable to figure out its relationsMp to the big picture. The following components are required: 1. Digital camera 2. Luminance meter 3. Known luminance box 4. The glare source 5. The task 6. The setting 43.1 DIGITAL CAMERA The digital still camera, which is used to capture image into digital form, has become common nowadays. There are many varieties to choose from. In this experiment, I used a JVC GR-DVL725U semi-automatic digital video/still camera with 1280 x 960 dpi resolution on digital still image. It is the recording tool used in this experiment to record all that the observer sees within their field of view (See appendix D for specification). Figure 4.1: The JVC GR-DVL725U. Figure 4.2: The Luminance Meter. 30 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 43.2 LUMINANCE METER The luminance meter is the tool used to measure the absolute luminance level or surface brightness. It is a camera-like tool, which has its own lens to focus on a surface and a trigger to initiate the measurement; the measurement unit is in foot- Lamberts (See appendix E for specification). 4 3 3 KNOWN LUMINANCE BOX The new Known Luminance Box is an 18”x l6 ”x8” box used as a standard of measurement in the experiment. It has two racks; the first rack is an absorptive cavity created by a black linen cloth and the second rack below it has a F8T5W fluorescent under cabinet lamp with a high-density opal glass diffuser. The cavity on the first rack was measured at 0 foot-lambert (fL) by the luminance meter, while the second rack with the fluorescent light was at 130 foot-lambert (fL). Having both known high and low absolute values, the known luminance box was placed within the digital imaging and used as a standard to determine other luminance or brightness levels within the image. Later, the known luminance box could be used as replacement of the expensive luminance meter. Moreover, it only needs to be recalibrated every 4 months due to the light loss factors of the lamp, which is the reduction factor of the luminance level caused by dirt, lamp life, etc. > s J '* 3 Figure 4.3: The Known Luminance Box. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 4.3.4 GLARE SOURCE The glare source is a 100 watt frosted halogen lamp equipped with a dimmer switch used to mimic the occurrence of discomfort glare in this experiment. It is the only component that acts as a dynamic variable and allows us to increase or decrease the luminance according to our needs. Figure 4.4: The glare source recorded on difference luminance level. 4.3.4 THE TASK The observers were asked to do a task on a computer with the glare source within their field of view. Tasks such as copying a printed article, doing quizzes and games on the computer were given to them in order to set their focus on the same main task focus. Subsequently, each time I increased the glare source luminance, a survey was given to them to evaluate their visual acuity and visual performance and whether or not they felt visually comfortable with the given condition. 4.3.5 THE SETTING For the setting, I laid out all of the components as arranged on figure 4.4. The digital camera was located behind the observer’s chair to record all the components within 32 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. the observant field of view. The known luminance box was placed outside the observant field of view, thus it did not intervene with the observer’s visual performance. Computer Monitor Known Luminance tlO Y Figure 4.5: The experiment setting. 4.4 THREE PHASES OF TESTING THE VISUAL AND DIGITAL METHOD Due to the degree of complexity, the plan of approach is divided into three phases. 1. Preliminary testing 2. Quantification testing 3. Validation process 33 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 4.4.1 PRELIMINARY TESTING In the preliminary testing, I tested the method to find the right setting and all of the different components/variables. The purpose was to diminish the possible flaws or errors during the beginning of the test and set up foundations for the next step. 4.4.2 QUANTIFICATION TESTING In the quantification testing, I tested and analyzed the visual and digital image data. The objective was to verify the digital computing quantitative analysis approaches used in this experiment. 4.4.3 SUBJECTIVE VALIDATION PROCESS The subjective validation process is the final testing that involves both qualitative and quantitative approaches. The qualitative approach validates the digital quantitative analysis processes by giving qualitative assurance on the occurrence of discomfort glare. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. C H A PTER V PRELIM IN ARY TESTING U SIN G TH E VISUAL AND D IG ITA L M ETH O D 5.1 THE OBJECTIVE OF THE PRELIMINARY TESTING Before starting an experiment, preliminary testing is necessary for evaluating the experimental methods. Upon evaluating each component and its potential results during the preliminary test, I gained more understanding in the relationship among the testing methods, contributing components and potential outcomes of the experiment. 5.2 THE INITIAL TRIAL In this first trial, I set all the components as described in the previous chapter (figure 5.1). I was the only subject who served as the observer in this first trial experiment. I recorded the experiment results on a piece of paper and input them into the computer whether I felt visual comfort or discomfort due to the luminance level of the glare source. A. Known luminance box B. The glare source C. Monitor Visual Task Area Fieure 5.1: The settine for the first trial exneriment 35 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. All other variables were set fixed, except the glare source was set in 6 different luminance levels at two minute intervals. After experiencing those 6 different luminance levels, I stated the degrees of visual comfort for each setting based on 5 degrees of visual comfort, which are unnoticeabie, noticeable, tolerable, disturbing and unbearable (figure 5.2). 1s t condition = Unnoticeabie 2 condition = Noticeable 4lh condition = Disturbing 3 condition = Tolerable 5th condition = Disturbing 6th condition = Unbearable Figure 5.2: The comfort rating felt on the 6 different luminance levels. 36 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. The entire digital image was recorded by a digital camera in JPEG format. Using Adobe Photoshop, I converted the JPEG file into grayscale mode and extracted the histogram from each digital image. Figure 5.3 below shows the histograms taken from those 6 different luminance levels. Lum ihosSy man 6523 Iw A Sid t o : 6331 Count M edian' 45 P&zrnm 1st condition = Unnoticeabie '.gia**fcjtumlno«^ : - ■ Lsygf■ C o u n t : : M s r c f i& E 2 Stdto: M efSan. 43 Parcemife. \ P B aa ls: 1223800 Caere Level1 t 3 r d condition = Tolerable 5 condition = Disturbing r W il ^ 3 : ,-------- Qmt&i 4a/nms%’ Ik - p g r : ! ' HSfe ] M ean: S3& G Uvei.226 1 Sid t o : 661 7 Cart. 12C B , M edian 33 Percents 33.75 : Pstefc 12289G G Cache leudi i timm o s i i y ' M e s n 7 1 5 8 Sid t o . 67.85 Cotfit M s f c a n : 4 5 P a r c s r & l e . U . : - C ^ L s v e ? : f ; 2 condition = Noticeable I M ean: 6364 SM tor 6624 1 M«S»t 33 Percssms’ . P»€is 1228800 Cache Lere* 1 4 condition = Disturbing ^iJsanreI j U um im sM y Zi Mean; 6247 S i d D e v ; m m mm; 3 7 Pm& 12288G0 U v e t ' ■ k : C o u f r t . Cache Uv-gf1 6 condition = Unbearable Figure 5.3: The histogram taken from the 6 different luminance levels. C n v m ri U i r t n o s K y Hjqrfa 37 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 5.2.1 THE INITIAL TRIAL ANALYSIS A histogram is a chart that shows the relationship between the pixel intensity level and the number of pixels at a certain intensity. The pixel intensity value is represented by the X-axis (ranging from 0 to 255; or dark to bright) and the number of pixels is represented by the Y-axis. The following picture is the histogram taken from the fourth condition. m m Figure 5.4: The image and histogram taken from the 4th condition luminance level. In the histogram, the overall background is represented by the rough bell curve on the left side. Where as on the right side, there are two spikes, which can be the known luminance box and the glare source. However, those two spikes which I could not identify brought up the question of how to determine which one is the known luminance box or the glare source. Another odd thing is the number of pixels in the spike in the histogram that changes as I analyze them from the first to the sixth conditions. First, it starts short and gets taller 38 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. slowly until it peaks at the fourth condition, then it gets shorter on the fifth and sixth condition. This phenomenon could be caused by the digital camera capability that auto adjusts the exposure of the camera. Despite the automated and practical benefits of current digital cameras, sometimes the camera’s automated features limit us on forcing the camera to perform manually. 5.2.2 LESSON LEARNED FROM THE INITIAL TRIAL To avoid the occurrence of the two spikes on the histogram, the known luminance box should be placed under the desk to avoid any interference with the observer’s field of view. The known luminance box should be located outside the observer’s field of view. The image to be processed is selected to remove the known luminance box and include only the observer’s field of view. Thus, the histogram of the selected image contains only one of the two spikes. The known luminance box is used only as a standard measurement for quantifying the intensity values of the luminance levels; it must not interfere with the observer’s visual performance. When I was recording the experiments on a piece of paper during the test, the known luminance box was within my field of view. It felt like there were two glare sources in the space. Figure 5.5: The known luminance box should be placed away from the observer’s field of view. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Another lesson learned in this experiment is that the exposure of the digital camera should be set to manual to record all images under the same exposure. Setting the digital camera to manual mode enables me to control the range in the histogram. The preliminary testing has become an important step in setting up a foundation for the next experiments, which are to quantify and analyze the histogram. 53 THE GLARE SOURCE LOCATION TEST The purpose of this test is to evaluate the location of the glare source with regards to the degrees of visual comfort due to the occurrence of discomfort glare. The test consists of two settings. In the first setting, the location of the glare source was located next to the monitor. Whereas, in the second setting, the glare source was moved further away from the main visual task area, but was still within the observer’s field of view. As shown in figure 5.6, the location of the glare source is moved further to the left side of the observer field of view. S f i* ’ * ■ , Figure 5.6: On the second setting, the location of the glare source was moved further to the left. 40 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Location is one of the key aspects for setting up the experiment. As I learned about the location of the luminance box from the previous trial, other questions were raised, such as where should I put the location of the glare source and the visual task area. Moving components in an experiment should be done step by step in orderly fashion. In this particular trial, the location of the glare source is the main variable that becomes my study. Like the initial trial, the luminance level of the glare source was changed into 6 different luminance levels. The visual discomfort rating was recorded, while I was doing a task in front of the monitor screen in two-minute periods. Below are the digital images taken from the first and second trial experiments using the manual exposure method. a p j a n n | 1s t Setting, 1“ condition = Unnoticeabie 2 Setting, 1s t condition = Unnoticeabie * i \4 f m w m ^'jwSwhim g 1s t Setting, 2n d condition = Noticeable 2n d Setting, 2“ condition = Noticeable Figure 5.7: The image the first and second settings with their visual discomfort ratings. 4 1 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. The 2 ‘ " Setting - - S T - K * W - v ■yM jm -: ^ ■ '• • jjS fiy * ? i * • '* * * •* < K f ^ - ^ i W - 4 F 1s t Setting, 3r d condition = Tolerable 2n d Setting, 3r d condition = Tolerable 1“ Setting, 4th condition = Disturbing 2n d Setting, 4th condition = Tolerable 1s t Setting, 5th condition = Disturbing 2n d Setting, 5th cond. = Slightly Disturbing Figure 5.7: The image taken from the first and second settings with their visual discomfort ratings (continued). 42 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 1st Setting, 6th condition = Unbearable 2n d Setting, 6th condition = Disturbing Figure 5.7: The image taken from the first and second settings with their visual discomfort ratings (continued). Here are the histograms taken from those digital images using adobe Photoshop. £ p *M r* Hi ; r . g a r e a k l tMntoostty . Z * I L 7 L j J ' M e » '3 4 B 8 Level: SWDev; 3 6 3 2 Count: M a t o 23 PercerstHa: i Pfeeefc: 2 4 300 cm l e n t : 5 Is * Setting, 1s t condition = Unnoticeabie 0sanmsl ■ la iS a s ify " M ’ IL E 5 S B * » * ^ Mean. 362 7 Level: ' Std Dev; 3531 Court: Median: 29 Pertartlte: P&8& 2430D Cache Level: 1 2n d Setting, 1s t condition = Unnoticeabie ■ ~ Q ia rre l u n m o w ty V M r ks i i m m 37,65 \ 3 7 2 £ Level: 181 C a r t ; 4 - Median, 31 P e r c e n t 3 3 4 9 ■ V : Cacfte le v e l 1 1s t Setting, 2n d condition = Noticeable QSZ3 Qsmek turranosw Meats: 38S 7 SSdOw: 375 2 Medan, an Pixels: 24303 2n d Setting, 2n d condition = Noticeable Figure 5.8: The histograms taken from the first and second settings. 43 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. .!■■■ - ^ 1 ■ ■ g h a r s r ^ J : : U j r o t t a s f t y y f ■ - a r ? i ■ L . i m m 4 4 3 8 le v e l - ' S f c lC * v ; 3 9 3 5 C o u n t; M f a & S S P e r c e n t s ^ . P f c « f c 2 4 3 0 Q c a c h e L e ^ s i: r ‘ , -------- v------------ M M — 1 I - S^snret! tumirostiy L Q O t “ s 1 ; m m - #277 147 J ; j . SM Dev: 4039 Count; 5 S ftBramtfe; m 3 I Pkefe 24300 Cache leva}; 1 I * 1s t Setting, 3 r d condition = Tolerable 2n d Setting, 3r d condition = Tolerable u r a f s o s ity gtennetii lumtoosay l e y s ) : ; Count; C s d s e L a ^ i; i 1s t Setting, 4th condition = Disturbing 2n d Setting, 4th condition = Tolerable • O s a m e i .' L u r s n o s i S y / - Ms*r'49.17 Iasi. : StdDw 4501 Count : M a te 38 Perorate P » * : 243G0 Cacfttuoei:; l l l i l i i i i i i i M m a m m 'J iZ C e l- J T r r o s H y L V • r w n I K m m : 5 0 4 4 - L e v e l : l \ S M O a v ; 4 7 4 1 C o u n t : msm. 3 6 P a r t a S T t t t e ; * P i x e l s : 2 * 3 0 G C a c h e L e v e l ; i * 1“ Setting, 5th condition = Disturbing 2n d Setting, 5th cond. = Slightly Disturbing Figure 5.8: The histograms taken from the first and second settings (continued). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ■ gassai; i Luminostty 3 3 J SttD ev, 46.13 M e d i a n ; 3 Pfc&& 24300 C o w # , FercwHfe. O f c h e ie * ! : i G O Q»nr«fc. 1 L«n^ios% Mearf S2B5 SM£»fc'<t9ES9 Median: 3 7 P S f C e n t f i S : P»cajS: 24303 1s t Setting, 6 condition = Unbearable 2n d Setting, 6th condition = Disturbing Figure 5.8: The histograms taken from the first and second settings (continued). 5.3.1 THE GLARE SOURCE LOCATION ANALYSIS Changing the location of the glare source influences the observer’s feeling towards visual comfort and performance in the second experiment. When the glare source is placed further away from the main visual task focus, the discomfort glare has decreased. In other words, our eyes become more tolerant of the glare source when we move the glare source further away in comparison to the first trial experiment. Based on the comparison of the visual discomfort degrees between the first and second experiments (table 5.1), placing the glare source further away makes the discomfort glare less severe. ;'T st'-condition 3ra condition ■ 5 ™ -condition Unnoticeabie-:;; Noticeable, - Tolerable disturbing: VUmoticeable Tolerable. Tolerable ■Slightly' Disturbing : Table 5.1: The degree of visual discomfort comparison between the first and second experiments. 4 5 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Another fact is that the background wall luminance level increases or decreases in correlation with the glare source luminance level. However, as the wall becomes brighter, the eye begins to accept it as background. These are the additional extraneous variables that add more complexity to the experiment. Thus, those variables need to be reduced and controlled. As shown in figure 5.8, the bell curve on the left side of the histogram has a low pixel quantity value (represented by Y-axis) and is distributed almost evenly on the horizontal (X-axis). This means that the overall background is being evenly illuminated. 5.3.2 DETERMINING THE GLARE SOURCE LOCATION The location of the glare source does have great influences on the degree of visual comfort. The further apart the glare source is from the main visual task focus within the field of view, the less the possibility is to experience discomfort glare. The sensation of experiencing discomfort glare is most likely greater when the glare source is closer to the visual task area. This does not appear (quantitatively) on the histogram. 5.4 THE QUALITATIVE APPROACH TESTING On this third trial, the testing was performed at the School of Architecture at the University of Southern California. It took place at the Clipper Lab, where many students were working at that time. The glare source was located right next to the 46 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. computer screen, and the known luminance box was located underneath the computer table to avoid any interference within the observer’s field of view. A. Known luminance box B. The glare source C. Monitor The observer’s field of view Figure 5.9: The setting for the third trial experiment There were 5 students who volunteered for in the experiment. Based on the five degrees of visual comfort, they were asked how they felt in terms of visual comfort while they were doing their own tasks. I increased the luminance level of the glare source every two minutes and asked them to give their ratings. Below were the results taken in the third trial. Figure 5.10: 1s t CONDITION LUMINANCE LEVEL o The glare source = 12.3 FL o The monitor screen = 6.6 FL o The known luminance box = 0.2 -182 FL (cavity - light) a Meant 74 46 „»v<rl sio u e w :B S U K R ! ■ m s s f c m p w n tis r. P e t e l s - mm C a S s u v s l- 1 Visual Comfort Scale ( 1 -- 2 - 3 - 4 ~ 5 ) Comfortable Discomfort Unbearable Student #1 1 Student #2 1 Student #3 1 Student #4 1 Student #5 1 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 5.11: 2 CONDITION S i l l LUMINANCE LEVEL o The glare source = 789 FL o The monitor screen = 10.9 FL o The known luminance box =0.2 -182 FL (cavity - light) Visual Comfort Scale ( 1 - 2 - 3 - 4 - 5 ) Comfortable Discomfort Unbearable — Student #1 2 Student #2 1 Student #3 2 Student #4 3 Student #5 1 Figure 5.12: 3 CONDITION i LUMINANCE LEVEL o The glare source = 2390 FL o The monitor screen = 16.3 FL o The known luminance box = 0.2 -183 FL (cavity ■ light) m m m m m m i-m Visual Comfort Scale ( 1 - 2 - 3 ~ 4 - 5 ) Comfortable Discomfort Unbearable i Student #1 Student #2 Student #3 Student #4 Student #5 1 1 2 1 2 48 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 5.13: 4th CONDITION ■ ■ ■ LUMINANCE LEVEL o The glare source = 5910 FL o The monitor screen = 16.7 FL o The known luminance box = 0.2 -183 FL (cavity - light) - Cnw et tf lf e s s ll ( T W l m J; r Mean S4-3& ‘ SMDsv S5S3 M sdsatv. m iem Count PercentIfe; ' Pmfr 81004 O tfttU ve*t Visual Comfort Scale ( 1 — 2 — 3 — Comfortable Discomfort 4 - 5 ) Unbearable Student #1 3 Student #2 2 Student #3 3 Student #4 4 Student #5 2 Figure 5.14: 5th CONDITION LUMINANCE LEVEL o The glare source = 8710 FL o The monitor screen = 16.3 FL o The known luminance box = 0.2 -182 FL (cavity - light) gum tf: luminosity M e a v 3 6 7 0 : SW D W -661? 1 r - f e t f i a r r 30 78228 : Visual Com fort Scale ( 1 - 2 - 3 ~ 4 - 5 ) Comfortable Discomfort Unbearable Comfort Ratings Survey Student #1 3 Student #2 2 Student #3 3 Student #4 4 Student #5 2 49 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 5.15: 6th CONDITION 0ev-.7O73 O iirel» 8 !-.2 Visual Comfort Scale ( 1 _ 2 - 3 - 4 - 5 ) Comfortable Discomfort Unbearable LUMINANCE LEVEL o The glare source = 12100 FL o The monitor screen = 16.8 FL o The known luminance box = 0.2 -182 FL (cavity - light) Student #1 Student #2 Student #3 Student #4 Student #5 4 2 4 4 3 Figure 5.16: T CONDITION LUMINANCE LEVEL o The glare source = 13800 FL o The monitor screen = 16.5 FL o The known luminance box = 0.2 - 182 FL (cavity - light) Uwefc - Count: PsrtanM e: C K » K L « * * Z . mffifxs P M te 81745 Visual Comfort Seale ( 1 - 2 - 3 - 4 - 5 ) Comfortable Discomfort Unbearable Comfort Ratings Survey Student #1 5 Student #2 3 Student #3 4 Student #4 5 Student #5 4 5 0 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 5.4.1 THE QUALITATIVE APPROACH ANALYSIS The third trial used the best location of each component. Placing the known luminance box underneath the table was necessary to avoid any interference with the observer’s field of view, whose main visual task was centered on the monitor screen. On the other hand, the glare source was located next to the monitor screen (Figure 5.17). The histogram that is extracted from the digital image has unexpected curve patterns. It does not show a smooth bell curve pattern on the left hand side and a spike on the right hand side, which would indicate glare according to the Schiler glare method (figure 5.18). The ratio of the median luminance between the glare source and the overall background, which is represented by the X-axis, is between 3:1 and 2:1 ratio. Thus, discomfort glare might be appearing in the space. F igure 5.17: A sample image taken from the 3r d condition of the third trial. The median of the overall background luminance The median of the glare source luminance ti L M J j I f X | m M e a n : ^42 S & O s v ; Count: CacfiftUwel: 2 b : h is between 3:1 and 2:1 Figure 5.18: A sample histogram taken from the 3rd condition of the third trial. 51 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. In addition, the survey based on the 5 volunteer students showed that there was discomfort glare in the space. Although, it was obvious that they experienced discomfort glare in some degree, but there were some discrepancies. The discrepancies were caused by the ambiguous discomfort rating answers that they gave on each condition given to them. They seemed to have trouble in understanding what discomfort glare was and how they felt the occurrence of discomfort glare. These are the list of observations that was given by the observers. 1. Most of the observers stated that it is hard to choose the discomfort rating based on the 5 points visual comfort scale ([l]Comfortable - [2] - [3]Discomfort - [4] - [5]Unbearable), because their judgments of each scale are relative. 2. One of the observers said that he only felt a little discomfort on all of the conditions given. 3. Most of them were confused about the definition of visual comfort. What is it? How do they determine the visual comfort rating? Those are the questions asked by them during the experiment. 5.4.2 LESSON LEARNED FROM THE QUALITATIVE APPROACH TESTING There are several things that need to be reconsidered in the next experiment. First, without sufficient knowledge and understanding of the discomfort glare behavior, it is hard to notice the occurrence of discomfort glare. Furthermore, it is more difficult to determine the visual discomfort rating based on the visual comfort scale. Second, the 52 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. initial purpose of this visual and digital glare analysis method is to predict the occurrence of discomfort glare in general conditions. The experiment in the computer lab room has a variety of surface materials and furniture. It is one of the general examples, where the visual and digital method is used to detect discomfort glare. However, those varieties of surface materials were assumed to cause the appearance of the unexpected curve pattern on the histogram. For instance, the reflective (specular) surface of the computer boxes reflected the light that came from the glare source and created secondary glare problems (figure 5.17). In other words, more variety of surface materials means more variables to be considered in the experiment. Those additional variables appear in the histogram as the unexpected curve pattern, which adds more complexity in the analysis. Thus, for the purpose of this particular experiment, it is useful to avoid the complexity of surface materials within the test environment. 5.5 SUMMARY OF FINDINGS The following final test conditions are the result of reviewing the flaws and lessons learned from the preliminary test. t » s S Figure 5.19: The Final Setting. I if n Figure 5.20: The observer’s field of view. 53 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. The monitor or the main task was located at the center area of the observer’s visual field of view. The overall background was set to create a controllable scene surrounded with walls that have the same reflectivity value. Less variety of reflectivity was preferable, because it reduced the complexity of the background luminance during the testing. The glare source was located close to the monitor within the observer’s visual field of view. The known luminance box was located under the desk and outside the observer’s visual field of view. On the other hand, the digital camera was set to capture all of the components including the known luminance box. It is necessary in this experiment to set the camera exposure and shutter speed to manual. 54 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER VI QUANTIFICATION TESTING 6.1 THE OBJECTIVE OF THE QUANTIFICATION TESTING The next phase after the preliminary testing was the quantification testing, which was used to verify the digital computing analysis and the experimental method. The digital computing analysis is the process where the recorded digital images are analyzed using known and affordable software, such as Adobe Photoshop 6.0, Microsoft Excel 2000 and Rascal Software 1.0. The verification testing consists of two main objectives: 1) Finding the relationship between the actual measured luminance levels and the pixel intensity values from the digital image data. In other words, the test compares the relative pixel intensity values of the image data with the absolute luminance measurement of the test setting. 2) Analyzing the behavior of the histogram whenever there is a change. 6.2 PREDICTING THE ABSOLUTE LUMINANCE LEVEL USING THE RECALIBRATION METHOD Recalibration is needed to ascertain the relationship between the absolute luminance values and the pixel intensity values. The absolute luminance values are measured using the luminance meter, whereas the pixel intensity values are taken from the 55 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. image data using image analysis software, such as Adobe Photoshop or Rascal software. The absolute luminance is measured in lumens per square foot or foot- Lamberts. The pixel intensity values are relative and range from 0 to 255. The recalibration testing has two components: The glare sources and the known luminance box. Below is the setting of the recalibration testing (figure 6.1). Description: 1. Glare Source 2. Cavity 3. Known Luminance Figure 6.1: The Recalibration Setting. The known luminance box has known cavity and known luminance levels. These two variables remain fixed at all times during the test. The known cavity level is recorded at 0.2 foot-Lambert by the luminance meter. In this particular test, the known luminance used an incandescent bulb. The known luminance level was verified using the luminance meter at 16 foot-Lambert. The known luminance level was set to a lower luminance level to set a significant difference between the known luminance level and the glare source. 56 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. There are 9 settings being recorded and measured. Each setting has a different luminance level on the glare source. Digital images are taken each time after the absolute luminance level is measured. Using both manual and automatic mode, the digital images were recorded. 6.2.1 THE RECALIBRATION METHOD USING MANUAL MODE In the manual mode, the digital camera was set using 1200x900 resolutions in JPEG format with under-exposure setting. The digital camera that uses RGB system records 3 grayscale images on red, green and blue color filters. Each pixel of the digital image carries those three different color values. Then, the digital image is transposed to a grayscale mode using Adobe Photoshop, which has only the luminance of black, grey and white. In the grayscale mode, each pixel has luminance, ranging from 0 to 255 luminance representing 0 as black and 255 as white. When Adobe Photoshop converts the color image to the grayscale mode, it will discard all of the color information by averaging all of those 3 grayscale values. Thus, it means that Adobe Photoshop determines the grayscale pixel value using the means of the red, green and blue values. Figure 6.2: The glare source at 0 foot- Figure 6.3: The glare source at 10 foot-Lambert Lambert (Manual mode). ('Manual model. 57 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 6.6: The glare source at 40 foot-Lambert (Manual mode). Figure 6.7: The glare source at 50 foot-Lambert (Manual mode). Figure 6.8: The glare source a t 60 foot-Lambert (Manual mode). Figure 6.9: The glare source at 70 foot-Lambert (Manual mode). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 6.10: The glare source at 80 foot-Lambert (Manual mode). Using the color sample tool from the Adobe Photoshop, the luminance of the glare source, known cavity, and known luminance are taken at exactly the same point as where the absolute luminance measurement was taken. C o l o r * Mea sure,me,nt j L a * — H I 1 1 MW □ s a Pixel Value Figure 6.11: The Adobe Photoshop color sample tool. Using the color sampler tool, the measurement cursor was pointed on the center of the glare source, cavity and known luminance. The pixel value is automatically shown in the info window. Below are the luminances for each surface. 59 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. j l l l f i f l i i i l l i i ' Source Source Pixet Cavity Pixel Luminance Known p u p Absolute Luminance i l w S B i l f i l i Pixel Value /0 FL 0 Q.2EL 16 FL 162 . 136 ‘ 164 20 FL 134 0.2 FT 0 16 FL m m m ' 219 0.2 FL ■ m m m i i i i p i m < » o f :. 222' 0.2 FL 0 16 FL 163 , 50 FL 252 0.2 FL m m s m l i l l l l l l f i 164 60 FL 254 0.2 FL 0 16 FL 163 70 FL 255 ; . . 0.2 FLs ■ i i i p i i i i .. 16 F L . 163 80 FL 255 0.2 FL 0 16 FL 163 Table 6.1: The comparison between the absolute value and the pixel value of the digital image (Digital images were recorded using the manual mode). After compiling the data on Microsoft Excel, it became clear that the relationship between the luminance and the actual luminance values was not a linear plot. The non linear relationship of the glare source was similar to an inverted logarithmic plot, as shown in figure 6.12. D The Glare Source Pixel Value Figure 6.12: The non-linearity relation between the pixel value and absolute luminance level of the glare source. 60 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Most current digital cameras use a light-sensing device called the Charge Coupled Device (CCD) to capture images. The CCD is illustrated as a chessboard, where each square consists of a photodiode, which is sensitive to light. Basically, it senses the amount of light coming to the surface and converts it to an electrical charge in the range 0 to 2 volts. The electrical charges will then be converted to digital signals, which can be read by the computer. The ranges will run from zero volts, representing no light, to the maximum of two volts, representing the brightest light. In the case of the eight-bit system, black is recorded as 00000000 or zero, and the brightest white as 11111111 or level 255. The pixel intensity value data captures the lower actual luminance level (0-60 foot- Lambert) well in a non-linear plot, but it compresses the data on the high end of the luminance levels (70 foot-Lambert and above). This limitation causes the pixel value to only represent the high luminance values (70 foot-Lambert and above) with the value of 255 maximum. In other words, all of the high-end luminance levels are flattened out at 255. Hence, the differences between the absolute luminance and pixel intensity value limit the ability of the digital data to represent the absolute luminance measurements. A high-end digital camera and better image data analysis software are needed to obtain more pixel intensity values. Most digital cameras and image data analysis software are designed to use the 8-bit system on the grayscale mode. Grayscale images generally use the 8-bit system that allows 256 different monochrome tones (2S =256). There are 61 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. systems in some medical applications that use a 10-bit system or more, but they are expensive and rare. The 10-bit system is capable of handling more monochrome tones (21 °=! 024 tones). 6.2.2 THE RECALIBRATION METHOD USING AUTOMATIC MODE The purpose of this testing using the automatic mode is to find the relationship among each variable, which are the known cavity, the known luminance and the glare source. In the automatic mode, the camera is capable of self-adjusting its exposure setting in achieving a good balance of luminance levels within the image. Initially, the known luminance and the known cavity were used as a standard ratio to calculate the absolute luminance value of each variable whenever the exposure setting changes. Figure 6.13: The glare source at 0 foot-Lambert (Automatic mode). Figure 6.14: The glare source at 10 foot-Lambert (Automatic model. Figure 6.15: The glare source at 20 foot-Lambert (Automatic mode). Figure 6.16: The glare source at 30 foot-Lambert Automatic model. 62 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 6.17: The glare source at 40 foot-Lambert (Automatic mode). Figure 6.19: The glare source at 60 foot-Lambert (Automatic mode). Figure 6.21: The glare source at 80 foot-Lambert (Automatic mode). Figure 6.18: The glare source at 50 foot-Lambert (Automatic mode). Figure 6.20: The glare source at 70 foot-Lambert ("Automatic mode). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Below shows the luminances for each surface compiled in Microsoft Excel. sill The Known The Know Source Cavity Pixel Absolute Luminance Luminance 0 F-l 12 0.2 FL 14 16 FL ' ■ 241 239 0.2 FL i S S i l S I S i - 16 FL. ” 241 20 FL 240 0.2 FL 14 16 FL 24? 30 FL 229 'M I S i B I S X i • ;16FL 23'- 40 FL 255 0.2 FL 14 16 FL 227 50 FL.' : •. 255: 14 .16 F t ■ 219 : 60 FL 255 0.2 FL 13 16 FL 219 70 FL. .. 255......... 2 2 i- . 16 FL I l l l M l S 8 0 FL 255 0.2 PL 14 16 FL 217 Table 6.2: The comparison between the absolute value and the pixel value of the digital image (Digital images were recorded using the automatic mode). The Absolute Luminance Values, The Glare Source Pixel Values and The Known Luminance Pixel Values 300 i i f l i p l i i i l i s S The Glare Source Pixel Value ■ The Known Luminance Pixel Value The Absolute Luminance Values Figure 6.22: The relationship among the absolute luminance values, the glare source pixel values, and the known luminance pixel values (Digital images were recorded using the automatic mode). 64 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. As seen in Figure 6.22, the automatic mode causes all of the luminances to increase in pixel values, although the absolute luminance values remain the same. Compared with the result that uses the manual mode (Table 6.1), most of the known cavity luminances have increased 14 points. The known luminance has increased in average of 66 points. However, as the value of the glare source absolute luminance increases, the known luminance pixel value decreases starting from the value of 241 to 217. The glare source luminance pixel values have also increased starting from 12 and flattened out at 255, but it is not linear nor logarithmic. This is assumed to be due to the fact that the camera self-adjusts so that the brightest surface in the image is set to 255, giving the broadest spread to the remarking values. As a matter of fact, the luminance of both the glare source and the known luminance are not linear with their absolute values nor inversely linear to each other, although the known luminance pixel decreases as the glare source value sets a higher maximum spread. Most likely, the non-linearity occurs because of the automation technology of the digital camera. Every digital camera has a built in light-meter device that determines how much light is needed to have a good picture. The light-meter device controls the exposure setting of the digital camera, particularly when the automatic mode is on. The digital camera that is used for this experiment has two light-meter characteristics, which are the center-weighted average metering system and the spot metering system. The center-weighted average metering system measures the viewing area and emphasizes the center portion (Figure 6.23). The spot metering system only measures the central spot area (Figure 6.24). Like most of the low-end digital cameras, the 65 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. digital camera that is used in this particular test uses the center-weighted average system. Figure 6.23: The center-weighted average Figure 6.24: The spot measurement system, measurement system. In this particular test, the camera used the center weighted average measurement system to self-adjust its exposure setting based only on the average of the central area luminance level. In other words, the camera disregarded all other luminance levels beyond the central area. The fact that the known cavity luminances were increased explains that the camera was adjusting its exposure setting to the average luminance value of the central area. Furthermore, the camera was set to capture more details in light within the central area, and neglected the other variables beyond it. Thus, the camera technology that was designed for ease of use actually ruins the data collection procedure in this particular testing. It may also be that the camera is expanding the middle range of intensities, not just the physical middle of the picture. The only anomaly in the data occurs at a glare source absolute luminance of 30 fL is read by the camera as intensity 229, while the 16 fL known luminance value is read at 234. 66 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 6.2.3 THE RECALIBRATION METHOD ANALYSIS The recalibration method has shown that there is a non-linearity between the absolute luminance value and the relative pixel value that represents it in the digital image. The non-linearity occurs because the common digital camera technology is limited in producing the right data collection process. Without a proper data collection process, finding the relationship between the absolute luminance level and the relative pixel value is useless. 6.3 ANALYZING THE BEHAVIOR CHANGE IN THE HISTOGRAM A histogram is a chart taken from the digital image that represents both the pixel intensity values (x-axis) and the number of pixels at the particular intensity (y-axis) of the digital image. It is important to remember that the x-axis represents the brightness intensity or pixel luminance value because we tend to think that the y-axis is representing the pixel luminance value. Figure 6.25: An image sample and its histogram. 67 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. When we take a look at the histogram above, the x-axis represents the pixel intensity values ranging from black (0) to white (255), while the y-axis represents the number of pixels of each luminance within the digital image. The big curve on the left indicates the ambient dark background, while the spike on the right describes both light sources. 6.3.1 ANALYSIS USING ADOBE PHOTOSHOP A number of settings with different luminance levels were created and the histograms of each setting were analyzed. All of the variables were set fixed (the known cavity and luminance) except for the desk lamp variable, which was flexible. The luminance meter measured each luminance level of the desk lamp on each setting. Figure 6.26: The 10 FL desk lamp. ' W B K m m ■ b I Figure 6.28: The 30 FL desk lamp. Figure 6.27: The 20 FL desk lamp. Figure 6.29: The 40 FL desk lamp. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 6.30: The 50 FL desk lamp. In Adobe Photoshop, the histogram can be easily acquired by clicking the histogram key under image on the menu window. The image should be in grayscale mode or lab color mode, where the lightness channel is set to “on” and the rest of the channel is “o ff’. Below are the histograms taken from each setting, starting with 10 foot- Lambert to 50 foot-Lambert. The left curve in shape of hill or mountain describes the overall ambient dark background. It is significant to note whenever there is an increase in luminance values on the desk lamp, the base of the bell shape curve on the left spreads out and shifts to the right. This means that the increasing luminance of the desk lamp brightens the overall background luminance. Channel- lightness L ..<*.... .1 Mean 5G74 atKsr&iW* • • • Level: ■ StdDev 5154 ' '.Count: • • • Median 33 .-Percentile; ; Pixels: 307700 . Cache Level: 2 . Figure 6.31: The histogram of the 10 FL desk lamp. : C h a n n e t ; ' T i g h t n e s s Mean 595 3 level: Stti Dav 5409 Count Median: 40 .. Percentile; Pixels 307200 cache level 2 Figure 6.32: The histogram of the 20 FL desk lamp. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Mean,- QGJ3S1 Level 5SiDev. 5 * 3 74 Count Median 45 Percentile Ptvels, 307200 Cache Level 2 -.X - Channel tigtttness j f " C tC 'tf J M M m m M m M M m m m m B ~ • ~ ' Meat 6862 mD&> 5653 Median: 5t PfcffllK 307200 L a M S t C c u p f Perce-vfite: •Cactetevel:-2- Figure 6.33: The histogram of the 30 FL desk lamp. Figure 6.34: The histogram of the 40 FL desk lamp. Mean- 7ZST ' Lever ■ ' StdOev. 5 436 Count- ; Median. 5 7 Percentife ' r ' : P - 3 0 7 ^ 3 0 . ^ c V C " - ■ ' : L ^ # e f c - S ', ; Figure 6.35: The histogram of the 50 FL desk lamp. The spike at the right describes that there is a bright light in contrast with the overall dark background, but it does not show any particular changes when the luminance level increases. There is no tangible data in the location of the known luminance and desk lamp. However, a new method is introduced to determine the location and change of behaviors of both light sources (known luminance and desk lamp luminance) as it appeared in the histogram chart, which is called the double layer method. The double- layer method uses Adobe Photoshop as a tool to locate the specific variables within the digital image and analyze them. 7 0 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Using the magic wand tools in Adobe Photoshop, I located, selected and copied the targeted desk lamp or the known luminance area from the digital image. Then, I created a new layer with the black background and pasted the targeted area. Afterward, a new histogram was taken from the new layer, which contained the location and pixel value of the particular variable. Finally, each histogram of each variable was layered all together on top of the initial histogram. ' Channel: Lightness • p t , - Channel- Lightness - - ; : ■j/'T "" : AT- ' { 1 1AV, J -■ :A 1 _J Mean S3 74 . Leveb v Mean. 53 93 Level; StdDev- SI 54 - C ount- ■ -.v StdDev 5409 ■ . Count: Median- 39 ;-Percenfi!e: '• • • • • • ., : Mgriian:'46 - : Percentile: Pixels: 30720Q . ■ Cache Level: 2 . •. . r. ' Pixeis;.-3D72aO Cache Level: 2 Figure 6.36: The double layered histogram of Figure 6.37: The double layered histogram of the 10 FL desk lamp. the 20 FL desk lamp. •> ■ ■ a Channel Lightness - o^ret Lightnas - - |';..13CJ 'r u ... ......- ...— i West 60CS • Level: . M eaniSasz.. - Level:. - StdDev 54 74 : Count1 ! ■ .SutDev: S5J5S-' Count i ■ ■ ■ ■ ; . Medial: 45 Percentile: ■ Median: 51: .. Percantife. Pweis. SO^GO . Cadre.Level; 2 Pixels: 3G72C0: Cache Level:. 2 . Figure 6.38: The double layered histogram of Figure 6.39: The double layered histogram of the 30 FL desk lamp. the 40 FL desk lamp. 71 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ppg iliiia ia i m M S Channe?: * ..... a a f j n j Mean 726? StdDev 5$9 6 Median 5 ? ; Pixels'. 3072GG-: A '--- Level: . CounI:; . ■ • Percenttie: Cache Level: Z ■ Figure 6.40: The double layered histogram of the 50 FL desk lamp. LEGEND: 1 = The initial histogram m m m = The desk lamp = The known luminance Using the double layered method, I analyzed the behavior changes of each variable and found out that the known luminance stayed the same in the shape of a spike on the right. However, there was a shift of pixel movement in the histogram when the luminance of the desk lamp increases. The shift was not in the shape of spike, but rather like a centipede that shifted to the right and then upward when it reached the right-bottom comer. 6.3.2 ANALYSIS USING CULPLITE A researcher at Ball State University, Jeff Culp, wrote a piece of software based on the Schiler glare method, called Culplite. Essentially, the program compiles the numerical data, which was acquired from the digital image, into a histogram and predicts the presence of discomfort glare based on the Schiler glare method. This was used to further analyze the image on this particular experiment. 72 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. All of the recorded digital images were first saved into .RAW file using Adobe Photoshop. The .RAW file consisted of the numerical data of the pixel coordinate and its pixel intensity values. Then, using the Rascal program, which was developed by David Schoen, the .RAW file was converted to ASCII code. As ASCII code data, the numerical data can be imported to Microsoft Excel, in which the numerical data, image graphics, and histograms were built. 240-280 200-240 160-200 88120-160 as 80-120 I t 40-80 @ 0-40 Figure 6.41: The sample image built from the .RAW file. The Culplite method analyses the histogram and tries to find the pixel intensity ratio of the overall background median and the spike median on the right side. As seen in figure 6.42, the big bell curve on the left represents the overall background, whereas the spike represents the light sources. Whenever the spike pixel intensity is 3 times or more than the median of the overall background, it detects the occurrence of glare within the image. According to the Culplite method, the glare free design should have 73 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. a ratio less than 1:2 between the median overall background and the spike pixel intensity value. Median Value 3 5 0 0 - T - - Background Bell Curve ' Low End Pixel Valve 5 High End Pixel Value .- -7& \ Background Median Value 42 Spike - i cw End Pixel Value 240 .-■■z-r- '-o -s.e /on Spike Median Value 255 Number of Baelcgroomi,Pixels 58914 ' Number of Spike Pixels' - 2943 Background Percentage of View 89.73 % Spike Percentage of View 3.83. % Spike Ip Background Ratio • ■ ■ • Median Spike to Median Background 8.07 TO 1 from Colplite. Y tS 74 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. This previous sample was taken from- the first setting, where the desk lamp actual luminance value was at 10 FL. The rest of the experiment was conducted as follows: 1. The desk lamp was the only variable that had an increment of 10 FL on each setting. 2. The known luminance box was fixed. 3. Digital image was taken on each setting. 4. Each image was saved as a .RAW file using the Adobe Photoshop software. 5. Afterward, the .RAW file was converted to ASCII code using the RASCAL software. 6. The ASCII code was imported to Microsoft Excel 7. Numerical data, graphics and histogram were extracted using the Culplite method. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 240-280 200-240 ^160-200 K120-1S0 SSS0-120 040-30 aaO-40 p iK - t i H M o f i a w -S m — Background Beil Curve ; Low End Pixel Value High End Pixel Value Background Median Value I » t 46 Spike' • ■ . • Low End Pixel Value High End-Pixel Value Spike M edian Value 240 255 255 Number of Background Pixels ' 70015 Background Percentage of View 91.17 % Number of Spike Pixels 3475 Spike Percentage o f View 4.52 % Spike to Background Ratio M edian Spike to M edian Background 5.54 TO 1 Schiler Glare ? YES Figure 6.43: The culplite analysis method on second setting (20 FL desk lamp). 76 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. v » : 160-200 25120-160 5*80-120 M x*l M 'te»§i«w Background Bell Curve Low End Pixel Value 8 High End Pixel Value 150 Background M edian Value 46 Spike ' • : Low End Pixel Value 230 H igh End Pixel Value 255 Spike M edian Value 255 Number of Background Pixels 71656 Number of Spike Pixels 381§ Background Percentage of View 93.30 % Spike Percentage o f View 4.96 Spike to Background Ratio M edian Spike to M edian Background 5.54 TO 1 Schiler G lare ? YES Figure 6.44: The culplite analysis method on the third setting (30 FL desk lamp). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 6.3.3 THE MEDIAN VS THE MEAN OF THE BACKGROUND LUMINANCE There is another visual comfort calculation method developed by Gregory Ward (LESO group EPFL and Radiance group LBL), which uses the RADIANCE synthetic imaging system. His program, which is called Find glare, locates the glare sources and computes the overall background luminance within the human visual field of view. In identifying the glare source, he uses the average value of the overall background luminance, multiplies it by 7 and sets it up as the threshold value. Whenever there is a pixel luminance that goes beyond the threshold value, his program automatically considers it to be the glare source. His choice of a threshold value equal to 7 is based on a crude test as producing a reasonable threshold for most scenes. Ward actually agrees that further studies are needed in order to determine the threshold value (Ward, 1990, June). There are three interesting factors in his experiment. The first factor is Ward’s concept of using the means of all luminance instead o f using the median value o f the overall background luminance curve. Essentially, the Ward method disregards the fact that the overall background luminance and the glare source luminance are two different variables, which is necessary for predicting discomfort glare. By using the means of all luminance within the image, Ward’s computational method combines all of those variables together. However, the overall background and the glare source luminance should be analyzed separately. Unlike Ward’s computational method, the Schiler glare method visually analyzed the median of the overall background luminance curve and 78 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. the median of the glare source luminance separately. Thus, the Schiler glare method should give more accurate analyses than the Ward method. The second factor is the sensitivity of the Ward method in predicting discomfort glare. The Ward method set a ratio of 1:8 as the new rule of thumb or standard to determine the occurrence of discomfort glare, whereas the Schiler glare method set a ratio of 1:3 between the median pixel luminance of the background and the glare source. Although the Ward method does predict the presence of discomfort glare by using the ratio of 1:8, the Schiler glare method would give a more sufficiently sensitive measurement on the occurrence of discomfort glare. Thirdly, further studies must involve the subjective approach or empirical surveys where a number of observers are invited to experience the space. It is true that each individual will not have the same response to the given experience, but a common ground value will be obtained after collecting the survey data. 6.4 SUMMARY OF THE QUANTIFICATION TESTING Below are several lessons learned from the quantification analysis testing: 1. The recalibration method confirms the non-linear relationship between the absolute luminance and the relative luminance. Both actual luminance and pixel intensity have different values and the relationship is not linear. The non- linearity, which is best described as similar to an inverse logarithm plot, compresses all the high-end pixel intensity values. 79 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 2. Recalibration could be achieved using higher technology equipment and better image data analysis software, but it is in contradiction to the initial hypothesis that uses the currently available and affordable technology. Furthermore, since it only becomes noticeable with ratios far beyond 7 to 1, it is not necessary to either method. 3. The known luminance box is not necessary since the ratios are relative and absolute values are not required. 4. The Schiler and Culp analysis method using the ratio between the median background luminance and the spike is more broadly applicable and may be more sensitive than any other methods. 80 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER VII SUBJECTIVE VALIDATION PROCESS 7.1 THE OBJECTIVE OF THE SUBJECTIVE VALIDATION PROCESS The validation process is needed to authenticate the whole process of the digital quantitative analysis. The validation process consists of subjective testing, which involves a number of observers who validate the presence of discomfort glare in a given space. The subjective test results will validate the digital quantitative analysis process by providing qualitative assurance on the occurrence of discomfort glare. 1.2 THE VALIDATION PROCESS OF THE SCHILER GLARE METHOD Based on the preliminary testing and the quantification testing, the final revised method was conducted with the requirements below: 1. The setting took place in a 12 x 14 feet room with the same reflectance value on each wall. 2. A computer, a desk and a chair were set within the human visual field of view. 3. A desk lamp, which was the only dynamic variable, was also placed within the human visual field of view. 4. There were nine settings, which were divided into 9 phases. The different luminance level of the desk lamp was set and measured in each phase. 5. There are 8 observers who gave their empirical opinions in a given space while doing a task in front of a computer screen. Each observer was asked to compete in playing 9 computer games, one at a time, in 9 different phases. 81 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Those games are Backgammon, Hearts, Free Cell, Tetris, Minesweeper, Solitaire, Checker, Spade and Pinball etc. They were told that it was a competition on speed, accuracy and score in completing the game. Each phase had a three-minute time limit; whenever they were done with their task in each phase, they were asked 3 simple “yes” or “no” questions. Every "yes" answer was worth 1 point, while "no” is 0. Those three questions were: 1. Did you feel fatigue in your eyes, while you were playing? 2. Did you feel discomfort visually? 3. Did you find any difficulty with visual focus on the game? Compared to R.G. Hopkinson who actually trained and educated the observers in advance so that they became familiar with discomfort glare, this test is more representative of the average observer. This approach was chosen to avoid biased answers and determine whether they had symptoms of discomfort glare while doing their task. These are the 9 setting with their luminance value measured by luminance meter: Figure 7.1: First Setting Figure 7.2: Second Setting (Desk lamp luminance = 4.87 foot-Lambert). (Desk lamp luminance = 9.8 foot-Lambert). 82 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 7.3: Third Setting (Desk lamp luminance = 14.8 foot-Lambert). Figure 7.4: Fourth Setting (Desk lamp luminance = 25.1 foot-Lambert). •1 Figure 7.5: Fifth Setting (Desk lamp luminance = 40.1 foot-Lambert). Figure 7.6: Sixth Setting (Desk lamp luminance = 75 foot-Lambert). Figure 7.7: Seventh Setting (Desk lamp luminance = 106 foot-Lambert). Figure 7.8: Eight Setting (Desk lamp luminance =152 foot-Lambert). 8 Figure 7.9: Ninth Setting (Desk lamp luminance = 175 foot-Lambert). 83 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 7.3 THE RESULT AND ANALYSIS OF THE VALIDATION PROCESS For the subjective test, I asked my friends to voluntarily help me out on my thesis. Most of them were in their mid-twenties. There were 2 females and 6 males, including myself, who were involved in this survey. We played one computer game at a time. Each time one of us finished the game or passed our three-minute time limit, they were asked several “yes” or “no” questions. Whenever I got “yes” as an answer, I added one point to the survey answer sheet. On the other hand, “no” answers equals to null or zero. When we moved to another computer game, I changed the setting with brighter luminance level on the desk lamp and asked them the same questions at the end of each setting. The survey data that I collected, regarding what they felt about the space while doing the given task, was featured in table 7.1. The table describes their qualitative answers towards the occurrences of discomfort glare in 9 different settings. According to the survey, most of the observers felt comfortable during the first and second settings. However, between the third and seventh settings, they started to have visual discomfort or discomfort glare. Finally, between the eight and ninth settings, they felt visually comfortable back again. I; .11 HI IV V VI VII VII I IX is®®! I I 2..DM you feel discomfort visually? T.; . • : d . 7 ... . 8 8 A. 6 ; 3 72 3. Did you fmd m y difficulty to get m m M E f I I B I P H ! 8 ; I S S S 1 3’ IPS!:i l l ’ visual feces ©iftiie game? ; Total;' 2 5 . 18 24. 24 ■ 2 4 . 16 8 6 Table 7.1: The validation survey result table. 84 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Discomfort Glare Survey 30 - o 3. D id you find any difficulty to get visual focus on the game? ■ 2. Did you feel discomfort visually? I I III IV V VI VII VIII IX a 1. Did you feel fatigue in your eyes, while you were playing? Settings Figure 7.10: The validation survey result chart. In some particular cases (IV - VII settings), they all agreed on having visual discomfort. However, there were some discrepancies on their answers about what they felt during the experiment, especially from the first to third settings and from the seventh to ninth settings. Those discrepancies were natural, because each observer had a different visual adaptation level towards the given space. The numerical data result (shown on figure 7.10) represented the general assumption of what the observer felt qualitatively during the experiment due to discomfort glare. Upon acquiring those qualitative data on the occurrence of discomfort glare; the digital data quantitative analysis was conducted. At the end of each setting, a digital image was taken and analyzed using the Schiler glare method. Within Adobe Photoshop, the digital image was cropped to represent the observer’s visual field of view, which was constructed based on the human cone of vision pattern (figure 7.12). 8 5 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Then, all cropped images taken from each setting were analyzed using the Culplite analysis method as described in chapter 6. The Observer field of view . Z Human Cone of Vision Figure 7.11: Setting the visual field of view. Culplite uses the Schiler glare method in analyzing a digital image to predict whether there is a discomfort glare within the image. The Schiler glare method analyzes the ratio between the median of the overall background luminance and the median of the glare source luminance that appears on the histogram chart. The overall background luminance is represented by the big bell curve on the left side of the histogram, whereas the glare source is represented by a spike on the right side of the histogram. Whenever the pixel value (intensity) of the median pixel value of the spike is three times greater than the median pixel value of the overall background, there will most 86 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. likely be discomfort glare within the image. Thus, if the ratio is 3:1 or more, there is definitely discomfort glare. If it is lower than 2:1, there is no discomfort glare. However, if It is in between 2:1 and 3:1 ratio, discomfort glare is likely to be present within the image. The Culplite test analysis result will be presented, including all of the items below: 1. The digital image of the represented visual field of view, 2. Pixel histogram, 3. The median value of both the overall background and spike pixel value, 4. The number of pixel of the overall background and spike, 5. The percentage of the amount of pixel on both the overall background and spike, 6. The median of the spike to background luminance ratio, and 7. The Schiler glare prediction. There were 9 test results, which are presented according to this order: M M jjg B tlf ItSMBIl SI1 1 1 8 1 M i i S VI 1 8 1 0 1 0 fX ’ 4.87 :fl4 i8 7 ■ ■ C C 7 5 r ' 152 VI757 F ff : ................ . O T t i P T ■ :FV' y ' . M K I B U S / 7,15 . ~ ' \ u l l ! ® 1 1 8 1 ! M S B Table 7.2: The list of figure numbers in relation to the setting number. 8 7 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Background Bel Curve Low En i tight End Pixel Value i ® 60 Spikes High;End:Pixel Value .255. Number of Background Pixels: 67175 ■ - Number of Spike Pixels : 4871 S p to f e m f e a f V i* * , 634 * Median Spike to Median Background . 6.10 TO 1 Figure 7.12: The First Setting (Desk Lamp Luminance = 4.87 foot-Lamberts). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Wm *I 1 Mwtpain 1 1 1 ■ s u m | | ( L ; ' 7/iL L U 4 s f- * f. - vkv '-.v ./t _ j. .-v':.' .- '- a ■ ■ ■ ■ : ’* * ? | i v] \ / a : \ ,v vV * M eat a ! » i ; ^ * * % n as % ■ $ S s ! n ! f § I ? ? i 1 ; J H ? ! ^ Background Bell €urve Low EndBixel Value ' 0 Higii EM Pixel Value . - B a c k g ro u n d M e d ia e V a lv e 4 5 Spike 11BBS8 High EM Pixel Value 255 Spike Median Vaine TAX Number of BackgrouM. Pixels 67232 Number of Spike Pixels 5783 5.38 : TO 1 Median Spike, to; Median Figure 7.13: The Second Setting (Desk Lamp Luminance = 9.8 foot-Lamberts). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. I mm Tv - « 8 G 0 f f ’ ; • & o $ i ; ■ U O O f f , r j ' \ ..A *sa»- ; : ::Bacbgrounfl;Beil Glrve / ; ; ; : ; High EndFixel Valfte 75 Background M Spike -Low End Pixel Vitae, 227; High End Pixel V alue,:.:;. . 255 |lj|§jj Number of Background Pixels 66976 Number of Spike Pixels . 6640 Median. Spike to Median Background . 4.72 TO T: I I H S I S ^ 1 llllll ■Hi Figure 7.14: The Third Setting (Desk Lamp Luminance = 14.8 foot-Lamberts). 90 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. u n i s Background Bell Curve L ovtf End Pixel. Value : : Uigh End. Pixel Value isli too l i ll Spile Low End Pixel Value 220 High End Pixel Value 255: Number of Background Pixels 67157 Number of Spike Pixels 75.87. Median: .Spike f o-Median Background . . .4.19 TO 1 Figure 7.15: The Fourth Setting (Desk Lamp Luminance = 25.1 foot-Lamberts). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. w a r n rlmi I 2 S S © x « i # l l l l l | f | | f § | | | | | | | » | | | | Background "Bell-Curve- Low Badn - ’: - High End Pixel Value ; 130 Spite ■ ■ ® t t i f i i i i s ® i High End Pixel Value 255 Number of Background Pixels 67132 -Number of Spike Pixels 7614 Background Percentage of View . S7,41 % • .Spike Percentage of View' - 9.9! Median Spike, to .Median Background 3.54 TO ! Schsier Glare * ? YES Figure 7.16: The Fifth Setting (Desk Lamp Luminance = 40.1 foot-Lamberts). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. r-r-— .. f* t» i ............' „ K m % 4 : I - I i » w l *"! , ,. . , ' ^ A , . I' m » I ! !\ I I J ' 1 - ! X / Background Bell Curve a i W W M W H H I M High End Pixel Value ' 160 :Spike : Low End Pixel Value High End Pixel Value 255 Spike Mediat- Value. 251 Number of Background Pixels 656.10 Number of Spike-Pixels 7606 llllkss iflfe; Median Sp&e te Median Background 2:.5; i TO! ' Schiler Glare ? ' , Figure 7.17: The Sixth Setting (Desk Lamp Luminance = 75 foot-Lamberts). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. PimtiSm0rMm sM | s a s s i A IP I « > i ! * “ ! n > • «.* m. .„ '» j I v I “ ! i W l A / n y r f k 7 — . , _ J . . *; . . . . . . . a ; ; . . . , . . . , , . , , . . a. , . . , . . . i .. .. . . -...... • . ■ . . . . . . . . . . . — _ . . ...'. I v . . . . . . j ;/ SOt i'” '■ ■ '1'iS; j^'.;;* ,. : ' . . I i 9 g S « ? 8 8 g 8 8 | g 8 § f § 8 f | | | | | | | | i | !% * * ¥ * » Background BeHSOprve Low End Pixel Value '23 . H igh End Pixel V a lu e : 190 Backg/ourtd M edian Value tt-8 Spike ■ H igh E nd Pixel Value g g l l i P t M i i g 255 ■ I ! N um ber o f B ackground Pixels 65889 SI# Number, .of Spike Pixels. 7386 Spike Pereeatagyof View ■ ..- * /< •,. Spike to Me(Uaa P"c1 tg*-ouhd ...2,13 TO 1 , -ScbBer Glare-? -'. MAYBE’ - ' - Figure 7.18: The Seventh Setting (Desk Lamp Luminance = 106 foot-lambert). 94 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. iV vv V \,\ Background Bell Curve Spike . to # Bad Pttet .Value 234 High End Pixel Value 212 : High End Pixel Valuer 255 .Background Median Value ,, v > llll f iil ll l ->250 Number of Background Pixels> 67201 Number of Spike Pixels:. 7716 MediamSpike to Median B 1.91 TO i ScMferGtore? '' * - NO Figure 7.19: The Eight Setting (Desk Lamp Luminance = 152 foot-Lamberts). 95 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. **30 r ■ s I " " I I i I «» 4 1 " % & 4 ; , |; - : I- i- - : - / .v v /i ''» ^ , V / '* - 1 S < S U S1 t ? 3 f f J * I f Background Bell Curve . Ipfp High End Pixel Value : 215 llililf Spike Low End Pixel Value High End Pixel Value 255 Spike Median Value --25 i Number of Background Pixels 67372 illfSI " Number of Spike Pixels 7320 . - - - 1 . ; ■ j§| Spike to Background Ratio Median Spike to Median Background : 1.90 TO 1 iliillS ^^^W ^B llilB ii ISM lllll Figure 7.20: The Ninth Setting (Desk Lamp Luminance = 175 foot-Lamberts). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. The table below (Table 7.3) shows the comparison between the Schiler’s glare prediction and the qualitative survey results in regards to the present of discomfort glare. Both the qualitative survey and Schiler’s quantitative theory indicate the existence of discomfort glare in the third to the seventh settings and no glare in the eight and ninth settings. Nonetheless, the theories show different result in the first and second settings. The Qualitative Versus Schiler's Glare Theory I II l i t IV V VI VII VIII IX Qualitative Survey no no yes yes yes yes yes no no Schiler’s : fib re yes yes yes yes yes maybe maybe no no Table 7.3: The comparison table between the qualitative and the Schiler quantitative glare theory. It is significant that those differences occur in the low luminance level settings (in particular on the first and second settings). Although the Schiler’s glare method indicates the existence of discomfort glare, the qualitative survey shows that there were none. There are several possibilities that explain how these differences happened. One reason might be that the glare source was too dim. The monitor luminance level was higher than the glare source. The computer screen, which was the main task focus of the observer, had become the background. For further analysis, Adobe Photoshop 97 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. had been used to search and isolate only the location of the glare source. This isolation method was used to separate the overall background and the glare source that appeared on the histogram. Using the magic wand tools, I isolated only the glare source, copied and pasted it on different layer (Layer 2). Thus, when the histogram was extracted from the image within layer number two, I got a bump on the right but not at the right- end (figure 7.24). It is significant that the bump represents the desk lamp or glare source, but it does not have the highest pixel intensity value. Thus, the glare source has lower pixel intensity level than the monitor. s ftormiri Figure 7.21: The glare source from the second setting was taken from the background. £ U n i i i e d 1 K :0 > : 'C 5 5 ” > 3 ! Figure 7.22: The glare source was placed on different layer. 98 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. - V < V" Figure 7.23: The original histogram of the second setting with both background and glare source together. Figure 7.24: The histogram o f only the glare source within the image. The monitor that serves as the observer’s main task focus has higher luminance value than the overall dim background. Since the monitor has captured most of the observer’s attention, it might become the background luminance level. In other words, the median value of the background might have been shifted to the median value of the monitor. Based on the data of the first and second setting, the histogram describes the overall background as a shape of bell curve on the left and several bumps on the right of the chart. Below is the histogram taken from only the overall background of the second setting. V i , , -v. - v ■ . . . ■ ' s ' - . Figure 7.25: The image taken from the second setting (without the glare source) 99 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. * ♦ - — - T Sie monitor I Figure 7.26: The histogram generated from figure 7.25. Another consideration is the fact that the overall background has the monitor (the observer’s main task focus), which also functioned as the glare source. It is possible to add another set of rules to the Schiler’s glare method, especially in this particular case. Whenever the observer’s main task focus has become the glare source or the brightest image within the image, the median value of the background might need to be reconsidered. The median value of the monitor might override the median of the dim background. Thus, in this particular case, the Schiler’s glare method will consider using the median of the monitor as the median background instead. Second, the number of pixels in the spike is too few compared with the overall background. According to the data on the first and second setting, the number of pixels of the spike is less than 9% of the overall background. As additional rule to the Schiler glare method, the number of spike pixels might be necessary to be more than 9% of the background pixels. 100 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. m m N n m h p r n f R a r tm r n iin ij P iyfslc M u m h p r n f .Qnilro PSyoSe t ■ «■ 5: ' Figure 7.27: First Setting (The number of spike pixels compared with the background pixels). sax • 4 8 8 - *§»- m m - H tm * m m S I I 8 1 § 1 I i ; H it H Num berof Background-Pixels Number of-.Spike.'Pixels Figure 7.28: Second Setting (The number of spike pixels compared with the background pixels). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 7.4 POTENTIAL FLAWS OF THE APPROACH Initially, the purpose of this testing is to validate the quantification approach by using the qualitative approach. However, there are several flaws regarding this subjective validation process. The flaws are listed as follows: 7.4.1 SMALL SIZE SAMPLE The first flaw is the small size sample. The number of observers who participated in this test is only 8 people. It should be at least 100 samples for the validation process. The small size sample is not enough to give any assurance that the quantitative approach is valid. Nonetheless, It is adequate to give us the big picture of what Is going on with the visual and digital methodology in finding the occurrence of discomfort glare. 7.4.2 RESEARCHER PARTICIPATION The other flaw is the researcher participation in the subjective validation testing. The researcher is not supposed to participate in this testing, because he would give a biased answer according to his expectation. 7.4.3 DEMOGRAPHICS The demographics of the participants consist of both male and female genders. Most of the participants are students who came from a variety of social cultures. However, the age range of the participants Is only within 20 to 30 years old. Initially, the age range was narrowed in order to reduce the number of variables and the complexity of 102 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. this particular testing. Thus, perhaps more complex demographics would be included in the future studies to ascertain a more complete and accurate validation testing. 7.5 SUMMARY OF THE SUBJECTIVE VALIDATION PROCESS Although the subjective validation testing is inadequate in terms of sample size, it does give enough understanding on a few things described below: 1. The subjective validation results were not exactly the same as the Schiler glare method results. 2. The discrepancies occur on the first and second setting when the luminance level of the glare source is dimmer than luminance level of the monitor screen. 3. The subjective validation result stated that discomfort did not exist on the first and second setting, while the Schiler glare method did. Further studies regarding this phenomenon that occurs on this particular case need to be addressed. 103 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER VIII CONCLUSION A visual and digital method is the best option to predict the occurrence of discomfort glare for its accuracy. Furthermore, the visual and digital analysis method works using common and affordable technology equipment and software. The quantification testing has concluded the following statements. First, the relationship between the actual luminance levels and the pixel intensity values is not linear. Second, it also concludes that a linear relationship is not entirely necessary. The occurrence of discomfort glare is predicted when the median luminance of the spike is three times of the overall background median luminance. The pixel intensity compression occurs at levels well above the glare threshold. Third, the change in the shape of the luminance distribution is more essential than the absolute luminance values. Fourth, the pixel intensity ratio between the median of the overall background and the median of the glare source is the key factor in predicting the occurrence of discomfort glare. In addition, this testing concludes that the known luminance box is no longer needed in this experiment, because it is no longer useful to predict the actual luminance level due to the non-linear relationship. 104 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. The validation process has verified that in some particular cases, the Schiler quantitative glare method does not correlate with the qualitative survey answers. Particularly, when the glare source luminance is dimmer than the computer screen, the Schiler glare method indicates the occurrence of discomfort glare in the given space, whereas the qualitative survey does not. There are two possibilities that explain how those differences occur. First, the histogram shows that the glare source pixel intensities shifted to the left of the computer screen pixel intensities, which means that the computer screen has become brighter than the glare source. The computer screen, which is the main task focus, becomes the background. The computer screen’s median luminance is considered to override the median of the overall background, because the computer screen has taken most of the observer’s focus. Nevertheless, more questions arise on how to determine which one of them we should use as the background and how to determine when the computer screen overrides the overall background. In addition, another consideration emerges on the pixel amount proportion between the spike and the overall background. It shows that the number of pixels in the spike shown in the histogram is too small compared to the overall background pixel amount. It is considered as a requirement of the Schiler glare method that the pixel amount proportion of the spike is at least 9 % of the overall background pixel amount. In conclusion, both qualitative and quantitative approaches have verified the process and methodology of the Schiler glare method to be more widely applicable and accurate to predict the presence of discomfort glare in a range of cases. However, 105 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. further studies need to be done to prove whether the method can be used in some particular cases where the possible glare source is dimmer than the main task focus. 106 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CH APTER IX FURTH ER R ESEA R C H The conclusions provide some insight that dictate further study and suggest other possible topics or avenues of investigation. Below is the statement indicating what further research could be done on this project topic. Further research in finding the relationship between the absolute luminance value and the relative pixel value is important in some particular cases, especially when the median of the overall background pixel value is above one third of 255. Based on the Schiler glare concept that discomfort glare occurs when the median value of the spike is three times higher than the median of the overall background, a new method of recalibration is needed for further investigation. Further research in finding the presence of discomfort glare in different settings is essential in order to prove that this visual and digital method is really useful across all circumstances to detect discomfort glare. Apparently, according to the conclusion, this method needs more in depth testing due to some particular cases where this method predicts discomfort glare where there is none in concordance with the qualitative survey. 107 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. The methodology of the visual and digital method provides a more sensitive and accurate prediction of the occurrence of discomfort glare. However, a validation process that includes more participants and more complex demographics is necessary for further testing. Further study is recommended on the use of this visual and digital method as a predictive tool for architects. A physical model or 3D computer rendering is a common practice used in the architecture field to study a space or building in the preliminary design stage. Using the visual and digital method to analyze the physical model or the computer-rendered image would set a further step for providing a useful application in avoiding discomfort glare in the architectural field. 1 0 8 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CH APTER X REFERENCES Busch, David D. (1995). Digital Photography. New York: MIS Press. Davies, Adrian & Fennessy, Phil. (1998). Digital Imaging for Photographers. Oxford, Great Britain: Focal Press. Dilaura, David L. (1976, July). On the Computation of Visual Comfort Probability. Journal of the Humiliating Engineering Society, Vol. 5. Egan, David M. & Olgyay, Victor W. (1983). Architectural Lighting. New York: Mcgraw-Hill Companies, Inc. Gordon, Gary. & Nuckolls, James L. (1995). Interior Lighting for Designer. New Jersey: John Wiley & Sons, Inc. Guth, S.K. (1966, October). Computing Visual Comfort Ratings for a Specific Interior Lighting Installation. Illuminating Engineering, Volume LXI. Hopkinson, R. G. (1963). Architectural Physics: Lighting. London, England: Her Majesty’ s Stationery Office. Hopkinson, R.G. (1957, June). Evaluation of Glare. Illuminating Engineering, Volume LIT. Kambich, D.G. (1991, Winter). An Alternative Relative Visual Performance Model. Journal of the Illuminating Engineering Society, p. 19. Rea, Mark S. (1986, Summer). Toward a Model of Visual Performance: Foundations and Data. Journal of the Illuminating Engineering Society, Vol. 15. Rea, Mark S. (1987, Winter) Toward a Model of Visual Performance: A Review of Methodologies. Journal of the Illuminating Engineering Society. Schiler, Marc. (1995) The American Solar Energy Conference: A method of Post Occupancy Glare Analysis for Building Energy Performance Analysis, w/ Shweta Japee, Minneapolis, MN. Schiler, Marc. (1992). Simplified Design of Building Lighting. New York: John Wiley & Sons, Inc. 109 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Schiler, Marc. (2000). 2n d EAAE — ARCC Conference on Architectural Research: Toward a Definition of Glare: Can Qualitative Issues Be Quantified? Paris, France. Ward, Gregory J. (1990, June) Visualization. Lighting Design and Application. Vol. 20, no. 6. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. APPEN D IX A: CALI U n iv ersity o f- S o u th ern C a lifo rn ia U n iv e rs ity Park I n s tjt u ti o n a l R eview B o a rd use CWVKRSITV MPA No. M-1299 O F S O U T H E R N Review of Research Involving Human Subjects APPROVAL NOTICE Date: November 22,2002 Principal Investkatoifs): Douglas Noble, Ph.D. / Jonathan Tedjakusama Office of the Provost u n iv e rsity P a rk Project Title: A Visual and Digital Method for Predictiae Discomfort Glare Based on Institutional Review ---------------- . . . ji Board (upirb) Quantitative and Qualitative Approach USC UPIKB #02-11-170 The University Park Institutional Review Board has reviewed the information you submitted pertaining to the above proposal at Its meeting o f N/A and has: QApproved study Educ Psych SocWk Socio Bus Armen [ Approved the Delegated Review Q D 0 D D D E Approved the Claim of Exemption L Approved continuation L Approved amendment Approved under the review by the chair; exemption: - 45 CFR 46.101 (b) (2) (Approved by Chair with conditions on November 6 ,2002) Conditions of Approval: The Investigators roust provide the following requested inform ation p rior to proceeding research (w hich includes contacting, recruiting, and enrolling potential subjects): Please note: This Claim of Exemption Approval Notice is valid for the fife of the study unless otherwise noted. An application for Continuing Review of a Claim of Exemption is not necessary unless there are changes to the study. In which case, an amendment to the original Claim of Exemption must be submitted to the UPIRB for review and approval. N O T E : The IRB m ust review all advertisem ents and/or recruiting m aterials. Serious adverse events, am endm ents and/or changes in the protocol must b e subm itted to the U PIR B for approval. C hanges m ay not be implemented until you have received the Board’s approval. Exception: changes involving subjects' safety m ay be implemented p rior to notification to th e U PIRB. Marlene S. Wagner, P U L , Chairperson University ot Southern California Los Angeles, California 90089-4019 Tel: 213 740 6709 Fax: 213 740 3919 e-mail: upirb@usc.edu 111 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. APPENDIX B: use UNIVERSITY O F SOUTHERN CALIFORNIA School of Architecture University of Southern California Watt Hail 204 Los Angeles, California 9C089-C29i Tel: 213 740 2723 fax: 213 740 8834 University of Southern California Master of Building Science (School of Architecture) CONSENT TO PARTICIPATE IN RESEARCH A Visual and Digital Method for Predicting Discomfort Glare Based on Quantitative and Qualitative Approach You are asked to participate in a research study conducted by DOUGLAS E. NOBLE, ALA, Ph.D. and JONATHAN TEDJAKUSUMA, from the Master of Building Sciences Program at the University of Southern California. The results o f this research will be contributed to his thesis or dissertation. Your participation is voluntary. A total o f 50 subjects will be selected to participate. Your participation is voluntary. L P U R P O S E O F T H E S T U D Y To leam the relation between the occurrences of discomfort glare and human visual comfort level. C P R O C E D U R E S If you volunteer to participate in this study, we would ask you to do the following things: You will be asked to fill out a questionnaire regarding the effect of various levels o f brightness to your eyes (comfort or discomfort) while you are doing your task in front o f the computer. There will be 6 different brightness levels conducted in every 5 minutes. And in between these phases, you will be asked to fill out the relevant question on the questionnaire. O P O T E N T IA L R IS K S A N D D IS C O M F O R T S There is a possibility you may feel discomfort to some degree due to the change in brightness. However, you have the right to stop the experiment immediately when you feel the discomfort is unbearable. | P P i 0 W E Date of Preparation: November 20, 2002 Inli m u m 1 i _____ HJ USC UPIRB #02-11-170 USC U N IV E R S IT Y P A R K IN S T IT U T IO N A L R E V IE W B O A R D 1 1 2 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 0 C O N F ID E N T IA L IT Y Any information that is obtained in connection with this study and that can be identified with you will remain confidential and will be disclosed only with your permission or as required by law. The only data of the observant that will be recorded is their age. When the results of the research are published or discussed in conferences, no information will be included that would reveal your identity. Forms containing names and other confidential will be locked in a locked cabinet and will not be recorded on any computer. We are not taking photographs o f any individuals. When the process is complete the confidential data will be destroyed by shredding The only people who have access are: 1. Professor Douglas E. Noble (Principal Investigator) 2. Jonathan Tedjakusuma (Student Investigators) 0 P A R T IC IP A T IO N A N D W IT H D R A W A L You can choose whether to be in this study or not If you volunteer to be in this study, you may withdraw at any time without consequences of any kind. You may also refuse to answer any questions you don’t want to answer and still remain in the study. The investigator may withdraw you from this research if circumstances arise which warrant doing so. □ ID E N T IF IC A T IO N O F IN V E S T IG A T O R S If you have any questions or concerns about the research, please feel free to contact Douglas E. Noble, AIA. PkD. (P.I.) at (213) 740 4589 or Jonathan Tedjakusuma (Co-P.L), at (562) 961-9235 or (626) 673-4172. 0 R IG H T S O F R E S E A R C H S U B JE C T S You may withdraw your consent at any time and discontinue participation without penalty. You are not waiving any legal claims, rights or remedies because o f your participation in this research study. If you have questions regarding your rights as a research subject, contact the University Park IRB, Office of the Vice Provost for Research, Bovard Administration Building, Room 300, Los Angeles, CA 90089- 4019, (213) 740-6709 orupitb@usc.edu. Date of Preparation: N o v e m b e r 2 0 ,2 0 0 2 USC UPIRB #02-11-170 P P i O f 1 R V h «f i i m b U S C U N IV E R S IT Y PA R K IN S T IT U T IO N A L A c V if-.v fiO A R t 113 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. SIGNATURE OF RESEARCH SUBJECT,, IARENT OR LEGAL KEfRESENTATTVE. " _________ I undeistand the procedures described above. My questions have been answered to my satisfaction, and I agree to participate in this study. I have been given a copy of this form. (J.________________________ Name of Subject Name o f Extent or Legal Representative (if applicable) Si: o f Subject, Parent or Legal Representative 4 /a] / z o o i Date -SIG N A T U R E QE INVESTIGATOR I have explained the research to the subject or his/her legal representative, and answered all of Ms/her questions. I believe that he/she understands the information described in this document and freely consents to participate. \fon^Jkg/\ [(UftiUvfiJMA ‘T of Investigator W /M 1240 $ o f Investigator Date (must be t subject’s) SIGNATURE OF WITNESS {If* « ! translator ismiesij My signature as witness certified that the subject or his/her legal representative signed this consent form in my presence as Ms/her voluntary act and deed. Name of Witness Signature of Witness Date (must be the same as subject’s) Date of Preparations November 20, 2002 USC UPIRB #02-11-170 h\ P P i e W E B ITU! Key U SC UMVKfiSirvftU' 114 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. I SIGNATURE' OF RESEARCH SUBJECT,.. PARENT " OR LEGAL REPRESENTATIVE. . ' ' - I understand the procedures described above. My questions have been answered to my satisfaction, and 1 agree to participate in this study. I have been given a copy of this form. IQOM &- I __________ NamwrfSroject 7 Name of Parent or Legal Representative (if applicable) e> 4 /an/£oc> 3 Signature of Subject, Parent or Legal Representative Date "" : ' ' I have explained the research to the subject or his/her legal representative, and answered all of his/her questions. I beieve that he/she understands the information described in this document and freely consents to participate. \).An<atbt*t Tedfalwouw. Name o f Investigator Signature of Investigator O jM fzao^ Date (must be the same as subject’s) SIGNATURE OF WHMESSipf aa oral tiraasfalif: jtensed) My signature as witness certified that the subject or Ms/her legal representative signed this consent form in my presence as his/her voluntary act and deed. Name of Witness Signature of Witness Date (must be the same as subject’s) fl P P i © W i " n i j Date of Preparation: November 29, 2002 M | . ...........! i/li! m 2 * m I I . ! f m 1 I USC UPIRB #02-11-170 U S C U N I V c R S iT Y R k f t K I f c i c V l T ! < • V • 115 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. SIGNATURE OF RESEARCH -SUBJECT, PARENT OR LEGAL REPRESENTATIVE. _______'' _______________ I understand the procedures described above. My questions have been answered to my satisfaction, and I agree to participate in this study. I have been given a copy of this form. Name of Subject Name of epresentative (if • 2! -£002 Parent or Legal Representative Date S IG N A T U R E ,0 F tW VEgttGATOR I have explained the research to the subject or his/her legal representative, and answered all of Ms/her questions. I believe that he/she understands the information described in this document and freely consents to participate. \ i omrfhw T tdjA kj/rom A .__________ Name of Investigator ____________________________^ A / / X 6 0y o f Investigator Date (must be the same as subject’s) SIGNATURE OF WITNESS (If w opal trmstatar is nsSfe) My signature as witness certified that the subject or his/her legal representative signed this consent fonn in my presence as his/her voluntary act and deed. Name of Witness Signature of Witness Date of Preparation: November 2 0 ,29 0 2 USC UPIRB #02-11-17© Date (must be the same as subject’s) USC UWIVtRSiTV -’ARK 116 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. SIGNATURE OR RESEARCH SUBJECT,. PARENT OR LEGAL- REPRESENTATIVE. v r : ' - I understand the procedures described above. My questions have been answered to my satisfaction, and I agree to participate in this study. I have been given a copy of this form. y l l y / m________________________ Name of Subject Name of Parent or Legal Representative (if applicable) SigBatSreo: Parent or Legal Representative g y f m /&$ Date SIGNATURE OF IN V E S T IG A T O R I have explained the research to the subject or Ms/her legal representative, and answered all o f his/her questions. I believe that he/she understands the information described in this document and freely consents to participate. Name o f Investigator - ^-Signature of Investigator °*f / m As Date (must be the same as subject’s) SIGNATURE OF WITNESS (If w r a l «®isslat»r: !sTss«)‘' My signature as witness certified that the subject or Ms/her legal representative signed this consent forni in my presence as his/her voluntaiy act and deed. Name of Witness Signature of Witness Date (must be the same as subject’s) Date of Preparation: November 20,2002 USC UPIRB #02-11-170 F 0 ¥ E H I I If]]: m n m . U S C U K iV E R S lT V 111 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. I understand the procedures described above. My questions have been answered to my satisfaction, and I agree to participate in this study. I have been given a copy of this form. G m ia M ft Name of Subject Name of Parent or Legal Representative (if applicable) Name 0 1 rarer Signature o f Si gnature o f Subject, Parent or Legal Representative Date M A i M - I have explained the research to the subject or his/her legal representative, and answered all of his/her questions. I believe that he/she understands the information described in this document and freely consents to participate. Name oflnvestigator ___________________________ v L M U i i______ Ssghature oflnvestigator Date (must be the same as subject’s) My signature as witness certified that the subject or his/her legal representative signed this consent form in my presence as his/her voluntary act and deed. Name of Witness Signature of Witness Date (must be the same as subject’s) Date of Preparation: November 20, 2002 USC UPIRB #02-11-170 N O V 22 * USC UNIVERSITY PARK STITUTiOKM. :<EY:r--; 80A 118 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 1 SIGNATORY OP RESEARCH ' SU B JEC fT PA»«NT OR LEGAL j HEF1ESEKTATWE. ' ' _ ____ ' 1 understand the procedures described above. My questions have been answered to my satisfaction, and 1 agree to participate in this study. I have been given a copy o f this form. < jfr u is G __________________ _ Name of Subject Name of Parent or Legal Representative (if applicable) - O V /Z //Q 3 Signature of Subject, Parent or Legal Representative Date SIGNATURE OF INVESTIGATOR I have explained the research to the subject or Ms/her legal representative, and answered all o f his/her questions. I believe that he/she understands the information described in this document and freely consents to participate. Name oflnvestigator ? ___________________________ 6q / u / * $ oflnvestigator Date (must be the same as subject’s) SIGNATURE OF WITNESS (If an oral trai» b l# r Is used.) My signature as witness certified that the subject or his/her legal representative signed this consent form in my presence as his/her voluntary act and deed. Name of Witness Signature o f Witness Date (must be the same as subject’s) Date of Preparation: November 20, 2002 DSC UPIRB #02-11-170 n lk\ WEB! ill H i {/u; w 22 m USC UN1 V £ R $ B ‘ - 1 1 9 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. SIGNATURE OF RESEARCH SUBJECT, BAREMfft-OR. LEGAL'. JMPRESENTA1WB,____________ _________________________________ I understand the procedures described above. My questions have been answered to my satisfaction, and I agree to participate in this study. I have been given a copy o f this form. ^ -v r n l'm r M ____________ Name of Subject Name(£Barent or Legal Representative (if applicable) ect, Parent or Legal Representative gy l x \ /<?s Date S IG N A T U R E f W IN V E S T IG A T O R , I have explained the research to the subject or his/her legal representative, and answered all o f his/her questions. I believe that he/she understands the information described in this document and freely consents to participate. \Jo n a Jkg j^ _______ Name oflnvestigator ______________________________ K g f a U s * ____ //S ignature of Investigator Date (must be the same as subject’s) SIGNATURE OF WITNESS (Ufa* oral transistor is «edL) My signature as witness certified that the subject or his/her legal representative signed this consent form in my presence as Ms/her voluntary act and deed. Name o f Witness Signature o f Witness Date (must be the same as subject’s) Date of Preparation: November 20, 2002 USC UPIRB #02-11-170 P P i © w / A \ » /A i; m u m : - ji^ ; bSC IM V FR SlT Y > v.RK 120 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. APPEN D IX C: THE VALIDATION SURVEY FORM DATE & TIME GAME DESCRIPTION Stort « k u o i c w ^ f a r t < t f l ■'flu. t ’ nw. ^ > vk>*v \ m . DM you feel fatigue in your eyes, while you wots playing? Did you fed discomfort visually? Did you find any difficulty with vised focus on fee game? - i p .... .... .......... r ^BEPS j . 1 - A ; t J'Jmny 0 6 6 2 1 % Grnhm 0 0 & 2 X /ao u 0 i & ° ! 0 6 0 f Smmva 0 0 0 If f . S o m A m . . 0 r> 1 HmJy 6 0 0 ■2J, f i Sb*t 0 0 0 n TOTAL 6 f I Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. THE VALIDATION SURVEY FORM DATE & TIME GAME DESCRIPTION m :; l i m m 1 > i i s s - . ’* £ ;, t £ ; f c - A - t Jon& ttwih- 0 0 5 0 SW SO '2 0 i 1 % u 0 a 0 f •Jo^nty 0 a D *1 46 ,8 0 0 9 ■ f W l r 6 0 & 1 4 ? 2 ., ft?) I S\i(m yk a 0 0 *?£>M 2.s 4 - 5fut . \ 6 1 Rlv.hO d S c v m J A . 1 D 0 l./z3,9&0 TOTAL Z S z. w /z I/** 3 > t > ?mWl£ {, SesM m Tkt 'timx. U««i ij y rm'eUih , O m tojktl itsrt wi*u. Did you fed discomfort visually? Did you find any difficulty wife visual focus on fee game? Did you feel fatigue in your eyes, while you were playing? 122 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. THE VALIDATION SURVEY FORM DATE & TIME GAME DESCRIPTION i£TT!W 4l T k . t i w i UwM "t is s s u m /k i. Did you feel &tigue in your eyes, while you wane Did you feel discomfort visually? Did you find any difficulty with visual focus on the game? V V V I t * ;A ■ m r n m m m m m m i ■jchtxny 1 1 i 4c) z } ) 0 0 £ XllO L D U i 1 i 4 6 0 1 1 0 V i ; i 0 L r J j 0 t ( iffa 4 S'f&rz S l 6 %z 1 0 Q i n j TOTAL f 7 Jo Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. THE VALIDATION SURVEY FORM ©ATE & TIME GAME DESCRIPTION C 1 W H SfTTlWCl Tkt v u » i» i« U r ^ ni^w An*« 3-w-Mok Awl touf . Did you feel fatigue in your eyes, wftile you woe playing? Did you feel discomfort visually? Did you find any difficulty with visuai focus on the game? V v V I S ■ w a ia it A V * C i« x w i ; i •Johmy t i r 1 Gfcvi)h ltv\ 1 i 1 G r J X lc to L j i i i 1 6 q • f W A / 1 i t 5"?T S 1 1 2-3 f 1 i i 1 0 9 ^ A fX A A . 1 i t 4 5 i ■Tfetne 1 r H ) % TOTAL 8 9 S> 124 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. THE VALIDATION SURVEY FORM DATE & TIME GAME DESCRIPTION o H in fo ^ -% tri'c C lerri&Q 3 B o tc e s t m * tiw jk seme during mwjte I j M ? b'mff. Did you feel fatigue in your eyes, while you were playing? Did you fed discomfort visually? Did you find any difficulty with visual focus on the game? Ml wpas - ' i n ; ’ . . • i i ' j * . v ' at 1 / f f 1oS " 2 Johmy f I ( £ 1 0 J X m X i 1 / % 2 -S * H 'O i* A y I 1 I c Jt/kajka^. 1 ) 1 c SaffrJA 1 \ 1 ^ 4 4 . A S \Ja a fO /A 1 1 f 2< \% \ S& +‘ / 1 } 2 1 ? TOTAL 3 < p 125 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. THE VALIDATION SURVEY FORM ©ATE & TIME GAME DESCRIPTION w s ■ * 'S O M ........; i •Jctimw 1 f ^,.242) 2 Xl4£l U 1 \ i 1.S5D 1 ! i i lh,2JG0 4 "Hmds/ i t f 4r?CT> T t i i I lt oao f c S w m y a i t i 10, ~fZD 4- p 1 I \ a r n m . 1 r i S £ < k trt f I J q e v f ? TOTAL 8 8 8 / 2 1 l(p? . , ,,, -j FoiwiiUtfnil t XwtK ieiTiMj J % xqzJ. m Wffc fc<tre (m J - x u w i i i m C m /t, Did you feel discomfort visually? Did you find any difficulty with visual focus oo the game? Did you feel fatigue in your eyes, wMle you were playing? 126 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. THE VALIDATION SURVEY FORM DATE & TIME GAME DESCRIPTION o y /z i / o $. HJ [X€VeNTH £€TTlft)G] 'B m eA e fh J v jk scgre. EM yon feel fatigue in yonr eyes, while you w as playing? Did yon feel discomfort visually? Did yon find any difficulty w it h visual focus on die game? y v V m f X i < u L i / f e 112. 2. ! 0 i d b 2 T vim y. . 1 / 0 M b i f 1 0 0 6 9 ~ 9 S k tt 0 1 f 8 f Q J W a v a . / I 0 3 8 f M l 7 , i f ) 5 5 ” 8 'T O K jly 1 1 0 l-f- / TOTAL 7 < 0 5 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. THE VALIDATION SURVEY FORM D A TE* TIME GAME DESCRIPTION O H h \ JjLG Z>& ^ F A c - n m ■ £ e m m S 's ttjm & j T k? <puu ^ hunJl m ktcjfk sunt Did you fed fatigue in your eyes, while you were plying? Did you feel discomfort visually? Did you find any difficulty focus on the game? v v v N lii . HI i \JomMjih » 0 6 ?I3> z. i 0 0 d q \ 3. X ia o U 0 f 1 64f 4 G & tZ u P tf M n 1 0 D i i 8 d 4 0 0 0 G Sfart 0 f 6 $ 1 2 - 4 SvfMAym I 0 0 6 8 4 3 £ e % j r & J j k ~ o ( 0 I2-IJ TOTAL 4 3 i Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. THE VALIDATION SURVEY FORM ©ATE & TIME GAME DESCRIPTION 1 ■JokuM-V 0 0 6 11- z X io jj'L i I 3 0 1 - 2 0 0 6 m 4 'J b m M m * . 0 1 f 10 S u$ W / a c y i 6 /I t, a l 0 0 £ .3 H tw j v i 0 e Jc> 8 JiW. 6' O ' i TOTAL i-- 2 'L OH f z . \ i C lOWTtf seTTlWCiJ Sfaidt W W j -wm fffU i4. m i-mnjjtt (J« o F . Did you feel discomfort visually? Did you find any difficulty with visual focus on the gain©? Did you feel fatigue in your eyes, while you were playing? VVV 129 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. A PPENDIX D: GR-DVL725U Product Specification • 1.02 Megapixel, 1/3.8" CCD • HG Digital Stills (1280x960/1024x768/ 640x480) • 700X Digital Hyper Zoom with Spline Interpolation • 110,000-pixel 2.5" High Resolution, 270-degree rotating LCD color monitor • Multi-Brand Remote Control • F I.8 Bright lens ® Digital CyberCam Video Camera • Black/White Viewfinder • Integrated auto light • MultiMedia Card/ SD Memory Card compatibility • 10X Optical Hyper Zoom • Digital Image Stabilizer • 16x9 Squeeze Mode • PCM Digital Stereo Audio • Snap Shot Modes: Full screen, Frame, Pin-up, Negative, Multi-Picture, 4- Frame / 9-Frame, Digital Still Output • Ms Lock ® Wide Mode • Manual focus, Exposure, and White Balance modes • Black Fader • Digital Wipes and Fades • Variable-speed Shutter (1/500,1/250,1/100,1/60 sec.) • High Density Image Recording, Mini DV NTSC (SD specifications) » BN-V408U 800 mAh Lithium-ion, High Capacity, rechargeable battery pack • Built-in AC Power Adapter/battery charger ® i.Link Digital Input/Output (IEEE 1394 compliant) DV in/out • USB High Speed Interface and software for Still Image Transfer & manipulation(PC/AT compatible) 130 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. • S-Video Output • CDROM Software:USB Driver, Digital Photo Navigator, Presto! Mr. Photo, Presto! PhotoAlbum, Presto! ImageFolio • Shoulder strap, Editing Cable, USB Compatible Cable, 8MB MMC • Audio Dubbing • Random Assemble Editing with digital effect/scene transition selections • 1 year parts, 90 days labor warranty • 1.23lbs (560g) • 3.5" (89mm) • 2.88" (73mm) • 6.58" (167mm) • Power 4.3 Watts using viewfinder 131 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. APPEN D IX E: MINOLTA LUMINANCE METER The Minolta Luminance Meter is a compact, digital meter for measuring the luminance of light sources or reflective surfaces. The TTL (through-the-lens) viewing system enables accurate targeting of the subject. The Luminance Meter is the property of University of California Los Angeles. Measuring range: Foot-Lambert: 0.01-99,900 fL Measurement angle: 1° Conversion Factor To cd/ft2 = x 1/n To cd/m2 = x 3.43 To asb = x 10.76 132 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. APPEN D IX E: C L A IM O F E X E M P T IO N ftm cipal.fevfistigator(s)/A dvisof: PROFESSO R D O U G ? A S N O B L E Telephone: f2 l3 ’ >740-45g9_________________________ Student fay estig g tarisV M P I: JONATHAN TE D JA K U SU M A Telephone: 15621961-9235______________________ TM e o f the Project: A V ISU A L AN D D IG ITA L M ETH O D FOR PREDICTING DISCOMFORT G LA RE BASED O N Q U A N TITA TIV E A N D Q U A LIT A T IV E APPR O A C H ES P onding Source ( if an y ):___________________________________ Department: A RCH ITECTU RE___________________ HAS. 210 B ld g .& R m /M C ^ S T B A C C T R ip jT O C O L OFTjH : P R O J E C T A N D IT S K IK E O S & Check below all item which are applicable to this project. AH sections m u s t h e com pleted. T® q a a llfy fo r exem ption, B oth a a n d b m u st be checked. 1. D oes the project involve a. □ O nly one o r more o f the follow ing ( I f applicable, check a. and one o r m ore below ) □ the study o f norm al educational practices in a n established educational setting? CL the use o f educational tests? 0 survey or interview procedures? 0 observation o f public behavior? V the collection o r study o f existing: (check all sources to be u s e 4 and circle the source i f it is available.) V data? □ docum ents? □ records? 0 pathological specim ens? 0 diagnostic specim ens? b . V no interventions or m anipulations o f die subjects o r their environments? I f both V and “b" a r e n o t checked, please explain: 2. D oes the subject population include 0 children? □ prisoners? □ pregnant w om en? 0 incom petent adults? □ fetuses? 0 abortuses? 'I N /A (not applicable) Q other persons w hose ability to give inform ed consent m y be impaired D only elected or appointed public officials and/or candidates for public office?_____________________: ______ 3. W ill data include any inform ation regarding subjects’ 0 illegal conduct? □ drug use □ alcohol use?D sexual behavior? O other sensitive conduct or behavior? V N /A (not applicable) I f any o f foe above are checked, explain briefly: I f the subjects’ responses w ere to becom e know n outside the research, w ould they 0 dam age the subjects’ financial standing? 0 dam age the subjects’ employabiKty? 0 result in criminal or civil liability for the subjects’? V N /A (not affect the subjects’ in any w ay)? If any o f the above are checked, please explain briefly: 5. W ill the collected data include subjects’ 0 addresses? 0 telephone num bers? V ages? D social security num bers? fj m arital status? □ ethnic background? D sex? D incom e? 0 N/A (not applicable) I f any o f the above are checked, give approxim ate num ber o f subjects involved, and briefly describe subject population: 6. W ill data be recorded by: 7. Will data be identified by 0 videotape/film ? □ audiotaps? 0 subjects’ nam es? V photograph? V written notes? Q codes linked to subjects’ identity by separate code key? C o tta:? Specify: 0 N /A (not applicable) V codes not linked to subjects’ identity? □ other? Specify: □ N /A (not applicable) I certify that this project is exempt from review by the University Fade institutional Review Board. ______ . ‘Exemption C ategory number must be present 1. Signature o f Student Investig; ^ a * * - .. . I I jal 2 . Delegated C oraniU ee C hair date 3. Signature o f Princ$&! Investigator University o f Southern California date 4. Signature o f University Park IRB Chairperson date University Park Institutional Review Board M C 4019 (213)740-6709 133 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. INSTRUCTIONS AND EXEMPTION CATEGORIES • Investigators claiming exemption from the University’s -requirements for review o f research involving the use o f human subjects are asked to complete the Claim of Exemption, inserting the appropriate Exemption Category numbers), and return it to die Office o f the Vice Provost for Research, ADM 300, Mail code 4013. A signed copy will be returned to you. E X E M P T IO N C A T E G O R IE S A. Projects which involve no element o f research are exempt from review by the University Park IRB. 46.101 (a), 46.102(e) B. Projects m which the only involvement o f human subjects, including research in which die only involvement o f children as subjects will be in one or more of the following, do not require review by the University Park IRB, unless die project involves research which includes vulnerable subject populations, such as: fetuses m& human In vitro fertilization for which Subpart B, of Part 46, Tide 45 o f the Code of Federal Regulations (CFR) provides special protection, 46.201 ~ 46.211 ; prisoners, for which Subpart C, o f Part 46 of 45 CFR applies, 46.301 - 46.306; and cM ldrn as research subjects, for which Subpart D, o f Part 46 o f 45 CFR applies, 46.401 -46.409. (1) Research conducted nt established or commonly accepted educational settings, involving normal educational practices, such as (a) research on regular and special education instructional strategies, or <b) research on the effectiveness of, or the comparison among instructional techniques, curricula, or classroom management methods. 46.101(bXU The above exemption is applicable to mentally handicapped individuals only if research involves no changes m S h e content, location, or procedures of instruction from those normally experienced by the subject. (2) Research involving the use of educational tests (cognitive, diagnostic, aptitude, achievement), survey procedures, interview procedures or observation of public behavior, unless: (a) information obtained is recorded in such a m anna that human subjects can be identified, directly or through identifiers linked to the subjects; and (b) any disclosure o f (he human subjects’ responses outside die research could reasonably place the subjects at risk o f criminal or civil liability or be damaging to the subjects’ financial standing, employability, or reputation. 46.101(b)(2) The above exemption applies to research with children or mentally handicapped individuals as follows: ® Research involving the use of education tests is exempt; » Research involving survey or interview procedures is not exempt; * Research involving observations of public behavior is exempt only when the investigator does nos participate in the observed activities. (3) Research involving the use of educational tests (cognitive, diagnostic, aptitude, achievement), survey procedures, interview procedures or observation of public behavior that is not exempt u n d a category (2), if: (a) th e human subjects a re elected cm * appointed public officials or candidates for public office, or (b) federal statue(s) require(s) without exception that die confidentiality of die personally identifiable information will be maintained throughout die research and thereafter. 46.101(feX3) (4) Research involving the collection or study of existing data, documents, records, pathological specimens, or diagnostic specimens, if these sources are publicly available, or if the information is recorded by the investigates* in such a manner that subjects cannot be identified, directly or through identifiers linked to fee subjects. 46.101(b)(4) (5) Research and demonstration projects that are conducted by or subject to the approval of federal department or agency heads, and that are designed to study, evaluate, or otherwise examine: (a) public benefit os service programs; (b) procedures for obtaining benefits or services under these programs; (c) possible changes in or alternatives to those programs or procedures; or (d) possible changes m methods o? levels of payment for benefits or services under those programs. 46.101(b)(5) (6) Taste and food quality evaluation and consumer acceptance studies, (a) if wholesome foods without additives are consumed, or (b) if a food is consumed that contains a food ingredient ai or below the level and for a use found to be safe, os agricultural chemical or environmental containment at or below the level found to be safe, by the FDA or approved by the £?A or fee Food Safety and Inspection Service o f the USDA. 46.J01(bX6) D EFIN ITIO N S: H UM A N SUBJECT: A living individual about w hom an investigator conducting research obtains (1) data through intervention or interaction with the individual, or (2) identifiable private inform ation. RESEA RCH : A system atic investigation designed to develop or contribute to generalizabie know ledge. University o f Southern California * University Park Institutional Review Board * MC4013 * (213)7406703 134 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
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Asset Metadata
Creator
Tedjakusuma, Jonathan
(author)
Core Title
A visual and digital method for predicting discomfort glare
School
School of Architecture
Degree
Master of Building Science / Master in Biomedical Sciences
Degree Program
Building Science
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
Architecture,OAI-PMH Harvest
Language
English
Contributor
Digitized by ProQuest
(provenance)
Advisor
Knowles, Ralph (
committee member
), Milne, Murray (
committee member
), Noble, Douglas (
committee member
), Schiler, Marc E. (
committee member
)
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-c16-313690
Unique identifier
UC11326980
Identifier
1420403.pdf (filename),usctheses-c16-313690 (legacy record id)
Legacy Identifier
1420403.pdf
Dmrecord
313690
Document Type
Thesis
Rights
Tedjakusuma, Jonathan
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the au...
Repository Name
University of Southern California Digital Library
Repository Location
USC Digital Library, University of Southern California, University Park Campus, Los Angeles, California 90089, USA