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Permanent link (DOI): https://doi.org/10.7939/R3H30J

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Multiview Video Compression Open Access

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Other title
Subject/Keyword
multiview video coding, 3D/multiview video, transcoder, distributed source coding
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Bai, Baochun
Supervisor and department
Prof. Janelle Harms
Prof. Pierre Boulanger
Examining committee member and department
Prof. Robert Laganiere, Information Technology and Engineering, University of Ottawa
Prof. Janelle Harms, Computing Science
Prof. Pierre Boulanger, Computing Science
Prof. Ivan Fair, Electrical and Computer Engineering
Prof. Anup Basu, Computing Science
Prof. Herbert Yang, Computing Science
Department
Department of Computing Science
Specialization

Date accepted
2009-10-02T19:55:57Z
Graduation date
2009-11
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
With the progress of computer graphics and computer vision technologies, 3D/multiview video applications such as 3D-TV and tele-immersive conference become more and more popular and are very likely to emerge as a prime application in the near future. A successful 3D/multiview video system needs synergistic integration of various technologies such as 3D/multiview video acquisition, compression, transmission and rendering. In this thesis, we focus on addressing the challenges for multiview video compression. In particular, we have made 5 major contributions: (1) We propose a novel neighbor-based multiview video compression system which helps remove the inter-view redundancies among multiple video streams and improve the performance. An optimal stream encoding order algorithm is designed to enable the encoder to automatically decide the stream encoding order and find the best reference streams. (2) A novel multiview video transcoder is designed and implemented. The proposed multiview video transcoder can be used to encode multiple compressed video streams and reduce the cost of multiview video acquisition system. (3) A learning-based multiview video compression scheme is invented. The novel multiview video compression algorithms are built on the recent advances on semi-supervised learning algorithms and achieve compression by finding a sparse representation of images. (4) Two novel distributed source coding algorithms, EETG and SNS-SWC, are put forward. Both EETG and SNS-SWC are capable to achieve the whole Slepian-Wolf rate region and are syndrome-based schemes. EETG simplifies the code construction algorithm for distributed source coding schemes using extended Tanner graph and is able to handle mismatched bits at the encoder. SNS-SWC has two independent decoders and thus can simplify the decoding process. (5) We propose a novel distributed multiview video coding scheme which allows flexible rate allocation between two distributed multiview video encoders. SNS-SWC is used as the underlying Slepian-Wolf coding scheme. It is the first work to realize simultaneous Slepian-Wolf coding of stereo videos with the help of a distributed source code that achieves the whole Slepian-Wolf rate region. The proposed scheme has a better rate-distortion performance than the separate H.264 coding scheme in the high-rate case.
Language
English
DOI
doi:10.7939/R3H30J
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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