IEEE CIT 2008

Keynote Speaker: Prof. David Suter, Monash University, Australia

Title:
High dimensional data analysis in computer vision.

Abstract:
Computer Vision (the study of extracting information from images that includes robot vision, smart video surveillance, multi-media image search, camera-based human computer interfaces, etc.) deals with very large data rates: but it generally also has to contend with high-dimensional data and incomplete data and noise. The basic tools underpinning much of contemporary computer vision research: clustering, large (and possibly incomplete) matrix factorization, regression/model fitting, manifold learning etc.; are tools common to many other branches of computing. In this talk, the author will draw upon examples from his own research work to outline recent advances in dealing with high-dimensional data. Illustrative applications will be given from computer vision problems (with some links made to other application areas)..

Brief Bio:
David Suter, Monash University, received the B.Sc. degree in applied math and physics from the Flinders University of South Australia in 1977 and the Ph.D. degree in computer vision from La Trobe University in 1991. His main research interests are: robust statistical methods, subspace based methods, motion estimation from images and visual reconstruction. He is a Professor in the Department of Electrical and Computer Systems Engineering, Monash University, Victoria, Australia.

He served as General Co-Chair for ACCV2002. He currently serves on the editorial board of three international journals: Journal of Mathematical Imaging and Vision; Machine Vision and Applications and the International Journal of Computer Vision. He has previously been on the editorial board of the International Journal of Image and Graphics.