TUTORIAL SPEAKERS

Title: MPEG Activities for 3-D Video Coding

Abstract: As the three-dimensional (3-D) video becomes attractive in various 3-D multimedia applications, ISO/IEC JTC1/SC29/WG11 Moving Picture Experts Group (MPEG) has recognized the importance of multi-view video for 3DTV and investigated the needs for standardization of 3-D video coding. In this tutorial lecture, we are going to cover the current MPEG standardization activities for 3-D video coding. After reviewing the basic requirements for 3-D video compression, we will cover various topics for multi-view video-plus-depth coding, including depth map estimation, prediction structure for multi-view video coding, and intermediate view synthesis at virtual viewpoints.

Bio: Dr. Yo-Sung Ho received the B.S. and M.S. degrees in electronic engineering from Seoul National University, Seoul, Korea, in 1981 and 1983, respectively, and the Ph.D. degree in electrical and computer engineering from the University of California, Santa Barbara, in 1990.
He joined ETRI (Electronics and Telecommunications Research Institute), Daejon, Korea, in 1983. From 1990 to 1993, he was with Philips Laboratories, Briarcliff Manor, New York, where he was involved in development of the Advanced Digital High-Definition Television (AD-HDTV) system. In 1993, he rejoined the technical staff of ETRI and was involved in development of the Korean DBS Digital Television and High-Definition Television systems. Since September 1995, he has been with Gwangju Institute of Science and Technology (GIST), where he is currently Professor of Information and Communications Department. Since August 2003, he has been Director of Realistic Broadcasting Research Center (RBRC) at GIST in Korea.
He gave several tutorial lectures at various international conferences, including the IEEE Region Ten Conference (TenCon) in 1999 and 2000, the Pacific-Rim Conference on Multimedia (PCM) in 2006, 2007 and 2008, the IEEE Pacific-Rim Symposium on Image and Video Technology (PSIVT) in 2006 and 2007, the 3DTV Conference in 2008, the IEEE International Conference on Image Processing (ICIP) in 2009, and the IEEE International Conference on Multimedia & Expo (ICME) in 2010. He is presently serving as an Associate Editor of IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT). His research interests include Digital Image and Video Coding, Three-dimensional Image Modeling and Representation, Advanced Source Coding Techniques, and Three-dimensional Television (3DTV).

Title: Histogram Intersection Kernel Learning for Multimedia Applications

Abstract: Histograms are used in almost every aspect of computer vision (from visual descriptors to image representations) and many other multimedia systems and applications. Histogram Intersection Kernel (HIK) and SVM classifiers are shown to be very effective in dealing with histograms. This tutorial will introduce the histogram representation in vision and other multimedia applications. This kernel has shown excellent performances in handling histogram data. We will introduce the histogram intersection kernel and show that it is either a positive definite kernel or a conditionally positive definite kernel in different domains (so that it can be used in various kernel learning techniques). One focus of this tutorial is to introduce fast methods for data processing and machine learning tasks involving the histogram intersection kernel. Based on the evaluation of a weighted sum of HIK expressions, we will introduce how kernel clustering and classification using histogram intersection kernel can be performed extremely fast and scales to large-scale problems. We will show example applications of the aforementioned techniques and show how the histogram intersection kernel behaves in non-histogram representations. Finally, we will also briefly introduce methods that approximate the histogram intersection kernel.

Bio: Jianxin Wu received the BS degree and MS degree in computer science from the Nanjing University, and his PhD degree in computer science from the Georgia Institute of Technology. He is currently an assistant professor in the School of Computer Engineering, Nanyang Technological University, Singapore. His research interests are computer vision, machine learning, and robotics. He is a member of the IEEE. He published papers in venues such as ICCV, CVPR, ECCV, ICML, NIPS, IJCAI, IEEE TPAMI, IJCV, and AIJ.