Recognition, Detection, and Analysis from Visual Information

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CIS Colloquium, Sep 26, 2008, 01:00PM – 02:00PM, Wachman 447

Recognition, Detection, and Analysis from Visual Information

Dr. Haibin Ling, Temple University, CIS Dept

Visual input is very important for human to understand and interact with the world. Computer vision, together with areas such as machine learning, medical imaging, and human computer interaction, aims to endow a computer the ability to see the world. In this talk, I will introduce several topics I have been working on along this direction, including shape matching, invariant local descriptor, category/object classification, face recognition, visual image summarization, histogram comparison, and human anatomy detection from medical imaging. First, I will give brief descriptions for most of the topics. Then, I will focus on category classification and medical imaging, which increasingly attract more and more research effort. In the first topic, proximity distribution is introduced to model geometric relation between visual patterns. In the second topic, I will describe our work on liver segmentation from 3D CT data.

Haibin Ling received the B.S. degree in mathematics and the MS degree in computer science from Peking University, China, in 1997 and 2000, respectively, and the PhD degree from the University of Maryland, College Park, in Computer Science in 2006. From 2000 to 2001, he was an assistant researcher in the Multi-Model User Interface Group at Microsoft Research Asia. From 2006 to 2007, he worked as a postdoctoral scientist at the University of California Los Angeles. After that, he joined Siemens Corporate Research as a research scientist. Since fall 2008, he has been an Assistant Professor at Temple University. Dr. Ling’s research interests include computer vision, medical image analysis, human computer interaction, and machine learning. He received the Best Student Paper Award at the ACM Symposium on User Interface Software and Technology (UIST) in 2003.