Multiview video compression

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 flelxible 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.