Recent research in learning and bargaining based video coding optimization


In the last decades, the problems of learning decision making strategy and optimizing the resource allocation process in video coding systems have received a lot of attention. However, these two problems are still challenging due to the limited theoretical analysis tools.

Machine learning is a hotspot and widely applied in artificial intelligence, pattern recognition and signal processing, since it learns from lots of information which we probably could name it as big data in today’s terminology. With this property, researchers attempted to apply this machine learning techniques to solve the decision making problem in video coding system for better performances. Besides, bargaining game theory has been proved to be a powerful technique for addressing the limited resource allocation problem among multiple players in the collaborative systems. Resource allocation problem in video coding system can be modeled as a bargaining problem, we attempt to investigate the optimal resource allocation strategy based on bargaining game theory.

In this talk, an overview of our recent research of learning and bargaining based video coding optimization will be presented. First, an overview on traditional video coding framework will be given and the fundamental optimization problems in video coding systems will also be discussed. Second, we will present the quad-tree coding unit (CU) depth decision process in High Efficiency Video Coding (HEVC) is modeled as a three-level of hierarchical binary decision problem. Then the flexible CU depth decision structure for each decision level are proposed to learnt about a model which will achieve better performances between the coding complexity and Rate Distortion (RD) performance. Third, we will talk about modeling the inner-layer bit allocation processes of spatial scalable video coding as bargaining problems. Then the bargaining game theoretic based approaches are proposed to solve the one-pass rate control optimization problems. Experiment results will be also presented to demonstrate the performance of our proposed approaches. Finally, we will discuss the potential optimization strategy for video coding system.


Prof. KWONG, Tak Wu Sam
Department of Computer Science
City University of Hong Kong, Hong Kong

Date & Time

15 Jan 2016 (Friday) 11:00 - 12:00


E11-4045 (University of Macau)

Organized by

Department of Computer and Information Science


Sam Kwong received the B.Sc. degree from the State University of New York at Buffalo, Buffalo, NY, in 1983, the M.Sc. degree in electrical engineering from the University of Waterloo, Waterloo, ON, Canada, in 1985, and the Ph.D. degree from the Fernuniversitaet Hagen, Germany, in 1996. From 1985 to 1987, he was a Diagnostic Engineer with Control Data Canada, where he designed the diagnostic software to detect the manufacture faults of the VLSI chips in the Cyber 430 machine. He later joined the Bell Northern Research Canada as a Member of Scientific Staff, where he worked on both the DMS-100 voice network and the DPN-100 data network project. In 1990, he joined the City University of Hong Kong as a Lecturer in the Department of Electronic Engineering. He is currently a Professor in the Department of Computer Science. He was responsible of the software design of the first handheld GSM mobile phone consultancy project in which it was one of the largest consultancy projects at the City University of Hong Kong in 1996. He coauthored three research books on genetic algorithms, eight book chapters, and over 200 technical papers. His book entitled Genetic Algorithm for Control and Signal processing published by Springer, London, was awarded as the Best Seller in 1997. He has been a consultant to several companies in telecommunications.

Prof. Kwong was awarded the Best Paper Award at the IEEE International Conference on Industrial Technology (ICIT’05), Hong Kong, in 2005. He also received the Best Presentation Award at the IEEE IECON 2004, Busan, Korea. He was the Invited Speaker at the IEEE 2001 ISIE Workshop in Busan, and the International Conference on Control, Automation and System held in Cheju, Korea. In addition, he received the Best Paper Award at the 1999 Bio-Informatics Workshop, Tokyo, in recognition of his outstanding contribution to the conference. Currently, he is the Associate Editor for the IEEE Transactions on Industrial Informatics, the IEEE Transactions on Industrial Electronics, Journal of Information Science. He also was associate editor of the Journal of Real Time Systems, from 2000 to 2010. He was also the Guest Editor of the IEEE transactions on Industrial Electronics, Feb. 2000.

Prof. Kwong has been heavily involved in organizing conferences and served closely to many IEEE Conferences and society activities. He is currently the Vice President of Conferences and Meeting of IEEE Systems, Man and Cybernetics Society. He is also a fellow of IEEE for his contributions on Optimization techniques for Cybernetics and Vide Coding.