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EFFICIENT MANAGEMENT TECHNIQUES FOR LARGE VIDEO
COLLECTIONS
by
Ping-Hao Wu
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Ful llment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(ELECTRICAL ENGINEERING)
August 2010
Copyright 2010 Ping-Hao Wu
Object Description
| Title | Efficient management techniques for large video collections |
| Author | Wu, Ping-Hao |
| Author email | pinghaow@usc.edu; pinhoramic@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Electrical Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2010-01-25 |
| Date submitted | 2010 |
| Restricted until | Unrestricted |
| Date published | 2010-06-03 |
| Advisor (committee chair) | Kuo, C.-C. Jay |
| Advisor (committee member) |
Ortega, Antonio Shahabi, Cyrus |
| Abstract | In this research, we focus on two techniques related to the management of large video collection: video copy detection and automatic video classification. After the introductory chapter and a brief review in Chapter 2, our main research results are presented in Chapters 3 and 4.; In Chapter 3, a fast duplicate video detection system based on the camera transitional behavior and the suffix array data structure is proposed. The proposed system matches video clips according to their temporal structures, which are represented by a set of frames corresponding to unique events, called anchor frames. Noticing the natural association between the camera operation and the resulting video, we use the camera transitional behavior to indicate the unique events. Specifically, shot boundaries and the begin and end points of camera panning and tilting movements are detected as anchor frames. The length between adjacent anchor frames is computed to form a one-dimensional sequence, called the gap sequence, which serves as the signature of the video. An efficient gap sequence matching algorithm based on the suffix array data structure is adopted to match two given video signatures, which can achieve linear-time processing. A candidate pruning stage is also proposed to reduce the computation as much as possible. Specifically, video clips that are very unlikely to be duplicates of the input query video are eliminated in this stage before the signature matching is performed. Experimental results show that the proposed framework is not only efficient (in terms of computational speed) but also effective (in terms of high accuracy) in identifying duplicate video pairs.; In Chapter 4, two novel features that take the shooting process into consideration are first proposed for video genre classification, which are the number of camera used in a short time interval, and distance of the camera to the shooting subject. Preliminary experiment results show that the proposed features capture additional genre-related information. Some conclusion about the genre can be inferred from the proposed features to a certain degree. Then the properties of amateur and professional video clips are observed and analyzed. Although a large amount of work has been proposed by considering cinematic principles, most extracted features are low-level features without much semantic information. In the proposed scheme, features are designed to take the camera operation and the nature of amateur video clips into account. These features address various differences in video quality and editing effects. They are tested on video clips collected from an Internet video sharing website, with several classifiers. Experimental results on this test video data set demonstrate that the camera usage can be inferred from the proposed features and, thus, reliable separation of professional and amateur video contents can be achieved.; Concluding remarks and future extensions are given in Chapter 5. |
| Keyword | duplicate video detection; video copy detection; suffix array; video classification; video database; camera operation; camera transition |
| Language | English |
| 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-m3108 |
| Rights | Wu, Ping-Hao |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Wu-3451 |
| Archival file | uscthesesreloadpub_Volume14/etd-Wu-3451.pdf |
Description
| Title | Page 1 |
| Full text | EFFICIENT MANAGEMENT TECHNIQUES FOR LARGE VIDEO COLLECTIONS by Ping-Hao Wu A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Ful llment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (ELECTRICAL ENGINEERING) August 2010 Copyright 2010 Ping-Hao Wu |
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