3D Video Coding and Transmission

Award Month: 
October - December 2015

3D video is a promising new media format. However, it poses challenges for the storage and transmission due to the large amount of data involved. This project will develop new and efficient algorithms for the compression and transmission of 3D video, using interdisciplinary theories from mathematics, signal processing, information theory, and communications. Compared to traditional single view video, 3D video has some unique properties, such as the availability of depth maps, view synthesis and the associated view switching. 

The project focuses on the following topics and tasks:
- Designing new 3D video coding schemes using the recently developed sparse and redundant signal representation theory, such as compressed sensing, K-SVD, and approximate message passing. The key idea is to find a sparse representation of the 3D video. 
-  Studying how to jointly optimize the encoding and decoding schemes to achieve different tradeoffs among distortion, storage cost, transmission rate, realtime computed frames, pre-computed frames, server-generated virtual views, and client-generated virtual views. 
- Exploring the impact of transmission error in the texture and depth maps on quality of the synthesized virtual view, and develop encoder-side algorithms to estimate the decoder-side distortion. This will optimize the encoding, for example, by applying smart error protection scheme at the encoder to improve the quality at the receiver.
- Studying the error propagation, the optimal concealment of depth map error, and the optimal design of error protection scheme for 3D video transmission.

About Project Leader: Jie Liang

Jie Liang received the B.E. and M.E. degrees from Xi'an Jiaotong University, China, the M.E. degree from National University of Singapore (NUS), and the PhD degree from the Johns Hopkins University, Baltimore, Maryland, USA, in 1992, 1995, 1998, and 2003, respectively. Between 1997-1999, he was with Hewlett-Packard Singapore and the Center for Wireless Communications (now part of the Institute for Infocomm Research), NUS. From 2003 to 2004, he worked at the Video Codec Group of Microsoft Digital Media Division. In 2012, he visited University of Erlangen-Nuremberg, Germany, as an Alexander von Humboldt Research Fellow.  

Since May 2004, he has been with the SFU School of Engineering Science. 

Professor Liang's research interests include Image and Video Coding, Multimedia Communications, Sparse Signal Processing, Computer Vision, and Machine Learning. He is currently an Associate Editor for the IEEE Transactions on Image Processing (TIP), IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), IEEE Signal Processing Letters (SPL), Signal Processing: Image Communication, and EURASIP Journal on Image and Video Processing. He is a member of the IEEE Multimedia Systems and Applications (MSA) Technical Committee and Multimedia Signal Processing (MMSP) Technical Committee , and is a Professional Engineer in British Columbia. He received the 2014 IEEE TCSVT Best Associate Editor Award, 2014 SFU Dean of Graduate Studies Award for Excellence in Leadership, and 2015 Canada NSERC Discovery Accelerator Supplements (DAS) Award.