COLLOQUIUM
Department of Computer Science and Engineering
University of South Carolina
 
Shape Matching and Classification: Algorithms and Performance Evaluation

 Song Wang
 Department of Computer Science and Engineering
University of South Carolina

Date: March 25, 2011 (Friday)
Time: 1430-1520 (2:30-3:20pm)
Place: Swearingen 2A31

Abstract

In this talk, I will present computational methods recently developed
for 2D shape matching and classification.  Specifically, I will first
introduce the shape context, inner distance shape context, and the
locally constrained diffusion process methods developed by different
research groups from the computer vision community. In the second part
of the talk, I will describe our recent work on improving shape
matching and classification using two perceptually motivated
strategies. All of these methods will be demonstrated using the MPEG7
shape data set and the Bullseye test for performance evaluation, which
will be also discussed in this talk.

Song Wang is an Associate Professor in the department of Computer
Science and Engineering at the University of South Carolina. He
received the PhD degree in electrical and computer engineering from
the University of Illinois at Urbana-Champaign (UIUC) in 2002. From
1998 to 2002, he also worked as a research assistant in the Image
Formation and Processing Group at the Beckman Institute at UIUC. In
2002, he joined the Department of Computer Science and Engineering at
the University of South Carolina. His research interests include
computer vision, medical image processing, and machine
learning. Dr. Wang is a member of the IEEE and the IEEE Computer
Society.