Face recognition: Opportunities and Challenges

March 17, 2006
Yu Hen Hu | University of Wisconsin – Madison, Dept. of Electrical and Computer Engineering

Human face recognition is a challenging biometric information processing task that has attracted much attention recently. The facial image of the same person varies with age, pose, lighting, facial expression, viewing distance, make-up, beard, or glasses. Practically every subject has “a thousand faces”. Finding an invariant feature that can map all these variations into few unique face feature vectors has been an on-going research topic for past 30 years. In this presentation, I will recent progress in face recognition research at UW-Madison face recognition group with specific focus on the systematic development of a novel class of 2D and 3D invariant features with respect to Euclidean transformation, and the application of these features to 3D facial recognition problems. Preliminary experimental results using Face Recognition Grand Challenge dataset will also be reported.

Speaker Details

Yu Hen Hu received BSEE from National Taiwan University, and MSEE and PhD degrees from University of Southern California. He was in the faculty of the Electrical Engineering Department of Southern Methodist University, Dallas, Texas. Since 1987, he has been with the Department of Electrical and Computer Engineering, University of Wisconsin, Madison where he is currently a professor.Dr. Hu’s has broad research interests ranging from design and implementation of signal processing algorithms, computer aided design and physical design of VLSI, pattern classification and machine learning algorithms, and image and signal processing in general. He has published more than 200 technical papers, edited several books in these areas.He has served as an associate editor for the IEEE Transaction of Acoustic, Speech, and Signal Processing, IEEE signal processing letters, European Journal of Applied signal Processing, and Journal of VLSI Signal Processing. He has served as the secretary and an executive committee member of the IEEE signal processing society, a board of governors of IEEE neural network council representing the signal processing society, the chair of signal processing society neural network for signal processing technical committee, and is the current chair of IEEE signal processing society multimedia signal processing technical committee. He is also a steering committee member of the international conference of Multimedia and Expo on behalf of IEEE Signal processing society. Dr. Hu is a fellow of IEEE.