"Visual Feature Extraction by Unified Discriminative Subspace Learning" by Dr. Yun Fu

Date: November 24, 2008
Time: 10:00 am – 12:00 pm

Room: BSB 3.02.02 ( oeffler Room)

Visual Feature Extraction by Unified Discriminative Subspace Learning
by Dr. Yun (Raymond) Fu (BBN Technologies)

Abstract:

Multimodality visual data analysis through discriminative subspace learning was an extensively discussed topic over the past several decades. It attracts much attention from interdisciplinary fields recently due to the increasing demand for developing real-world human-computer interaction and computer vision systems. A large family of subspace learning methods has been designed in the pattern recognition field based on different motivations and objective functions. Although they are diversified, it is intuitive to uncover some common ideas from them. Can we unify them and formulate new algorithms to further enhance the discriminating power for feature extraction? Stemmed from this motivation, a unified framework of discriminative subspace learning will be presented in this talk.

Based on the proposed general framework, several new subspace learning algorithms are designed. Those methods are successfully applied to real-world applications of face biometrics, such as face recognition, head poseestimation, realistic expression/emotion analysis, human age estimation, and lip reading.

Bio:

Dr. Yun (Raymond) Fu received the B.Eng. degree in information engineering from the School of Electronic and Information Engineering, Xi'an Jiaotong University (XJTU), China, in 2001; the M.Eng. degree in pattern recognition and intelligence systems from the Artificial Intelligence and Robotics Institute (AI&R), XJTU, in 2004; the M.S. degree in statistics from the Department of Statistics, University of Illinois at Urbana-Champaign (UIUC), USA, in 2007; and the Ph.D degree in Electrical and Computer Engineering (ECE) from ECE Department, UIUC, USA, in 2008.

From 2001 to 2004, he was a research assistant at the AI&R at XJTU. From 2004 to now, he was a graduate fellow and research assistant at the BeckmanInstitute for Advanced Science and Technology, ECE department and Coordinated Science Laboratory at UIUC. He was a research intern with Mitsubishi Electric Research Laboratories, Cambridge, MA, in summer 2005; with Multimedia Research Lab of Motorola Labs, Schaumburg, IL, in summer 2006. He jointed BBN Technologies, Cambridge, MA, as a Scientist in 2008 to build and lead the computer vision and machine learning team.

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