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. / Computer Networks and Multimedia Systems
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:AEU.10048/744 |
| Date | 11 1900 |
| Creators | Bai, Baochun |
| Contributors | Prof. Janelle Harms, Prof. Pierre Boulanger, Prof. Janelle Harms, Computing Science, Prof. Pierre Boulanger, Computing Science, Prof. Anup Basu, Computing Science, Prof. Herbert Yang, Computing Science, Prof. Ivan Fair, Electrical and Computer Engineering, Prof. Robert Laganiere, Information Technology and Engineering, University of Ottawa |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 8973080 bytes, application/pdf |
| Relation | B. Bai, P. Boulanger, and J. Harms, "An efficient multiview compression scheme", in Proc. of IEEE International Conference on Multimedia and Expo (ICME) 2005, 2005., B. Bai, P. Boulanger, and J. Harms, "A multiview video transcoder", in Proc. of the 13th ACM International Conference on Multimedia (ACMMM 2005), Singapore, 2005., B. Bai, L. Cheng, C. Lei, P. Boulanger, and J. Harms, "Learning-based multiview video coding", in Proc. of the 27th Picture Coding Symposium (PCS 2009), Chicago, Illinois, USA, May 2009., B. Bai, Y. Yang, P. Boulanger, and J. Harms, "Symmetric distributed source coding using ldpc", in Proc. of the IEEE International Conference on Communication (ICC 2008), Beijing, China, 2008., B. Bai, Y. Yang, C. Lei, P. Boulanger, and J. Harms, "Symmetric distributed multiview video coding", in Proc. of the 34th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009), Taipei, Taiwan, 2009. |
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