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Compositing Real and Virtual Objects
with Realistic, Color-Accurate Illumination
by
Chloe LeGendre
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements of the Degree
DOCTOR OF PHILOSOPHY
(Computer Science)
August 2019
Copyright 2019 Chloe LeGendre
Object Description
| Title | Compositing real and virtual objects with realistic, color-accurate illumination |
| Author | LeGendre, Chloe Anne |
| Author email | legendre@usc.edu;chloelle@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Computer Science |
| School | Viterbi School of Engineering |
| Date defended/completed | 2019-06-07 |
| Date submitted | 2019-08-02 |
| Date approved | 2019-08-05 |
| Restricted until | 2019-08-05 |
| Date published | 2019-08-05 |
| Advisor (committee chair) | Debevec, Paul |
| Advisor (committee member) |
Barbic, Jernej Fink, Michael |
| Abstract | In digital compositing, images from a variety of sources are combined to form a seamless, realistic result that appears as though it could have been photographed in the real world. This technique is extensively used in visual effects and film production, for example when an actor filmed in a studio is composited into a different real or virtual environment. It is also widely used in augmented or mixed reality, where rendered virtual imagery is combined with a live video feed. For a realistic and convincing composite, the content from the various source images must appear to have been captured at the same time under the same lighting conditions. Thus, whether such content is photographed or synthetically rendered, digital compositing benefits from accurate measurement of scene illumination, and, for rendered objects, also from accurate material reflectance measurement. In this dissertation, we therefore present new techniques for the measurement and estimation of illumination and reflectance, geared towards the goal of producing realistic and color-accurate digital composites. ❧ First, we present a multispectral illumination measurement and playback technique to extend studio lighting reproduction for live-action compositing to the multispectral domain, improving color rendition as compared with previous work. Next, a theoretical analysis affords the selection of an optimal, minimal set of light emitting diodes (LEDs) of distinct spectra for this technique. For post-production methods, we extend image-based relighting to the multispectral domain for the same goal of improved color rendition, forming the appearance of an object in a novel lighting environment by combining images of the object as lit by an omnidirectional, multispectral lighting basis. We show one real-world application of multispectral image-based relighting where color accuracy is critical: military camouflage material evaluation. For another specific application of digitizing humans, which enables rendering a person under a novel viewpoint or lighting environment, we also present an efficient approach to multispectral high-resolution facial scanning using monochrome cameras, where both geometric resolution and color rendition are improved compared to previous work. ❧ The final technique we present is a machine learning based method to estimate high dynamic range (HDR), omnidirectional illumination given only a single, unconstrained mobile phone image with a limited field-of-view. As image formation using the aforementioned post-production techniques requires accurate lighting measurement, typically realized using panoramic HDR photography and a special color calibration target, real-time mobile mixed reality compositing with convincing illumination remains elusive because these off-line light measurement techniques are both impractical and not accessible for the average mobile phone user. Our learning based approach for omnidirectional HDR lighting estimation from a single image is the first to generalize to both indoor and outdoor scenes, while comparing favorably to previous methods developed to handle only a single class of lighting. |
| Keyword | compositing; lighting reproduction; computational illumination; lighting estimation; multispectral imaging; multispectral illumination; computer graphics; material appearance capture |
| Language | English |
| Format (imt) | application/pdf |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m |
| Contributing entity | University of Southern California |
| Rights | LeGendre, Chloe Anne |
| Physical access | 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 author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given. |
| Repository name | University of Southern California Digital Library |
| Repository address | USC Digital Library, University of Southern California, University Park Campus MC 7002, 106 University Village, Los Angeles, California 90089-7002, USA |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-LeGendreCh-7736.pdf |
| Archival file | Volume11/etd-LeGendreCh-7736.pdf |
Description
| Title | Page 1 |
| Full text | Compositing Real and Virtual Objects with Realistic, Color-Accurate Illumination by Chloe LeGendre A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements of the Degree DOCTOR OF PHILOSOPHY (Computer Science) August 2019 Copyright 2019 Chloe LeGendre |
