CS Distinguished Lecture: Larry Davis, Computer Vision: History and Challenges

Monday, April 8, 2013 ( 2:00 pm to 3:00 pm )

Location: E222

Title: Computer Vision: History and Challenges

Speaker: Dr. Larry Davis (University of Maryland)

Time: Monday, April 8th, 2:00pm-3:00pm

Location: E222

Host: Gang Hua

Abstract:

The field of computer vision was started in the 1960ā€™s, in large part driven by applications in document image analysis (mail sorting). Fifty years later, there are many thousands of researchers and engineers around the world conducting fundamental and applied research in computer vision in applications areas ranging from astronomy to zoology. The talk will begin with an overview of the field from an applications perspective, highlighting some of the successes and open problems in a variety of application domains. Then, I will turn to one of the central and fundamental research problems in computer vision ā€“ how to develop computer vision algorithms that can recognize everyday objects in images and videos ā€“ and present approaches, progress and major challenges to solving this problem.

Biography:

Larry S. Davis received his B.A. from Colgate University in 1970 and his M. S. and Ph. D. in Computer Science from the University of Maryland in 1974 and 1976 respectively. From 1977-1981 he was an Assistant Professor in the Department of Computer Science at the University of Texas, Austin. He returned to the University of Maryland as an Associate Professor in 1981. From 1985-1994 he was the Director of the University of Maryland Institute for Advanced Computer Studies. He is currently a Professor in the Institute and the Computer Science Department. He was named a Fellow of the IEEE in 1997 and of the ACM in 2013.

Prof. Davis is known for his research in computer vision and high performance computing. He has published over 100 papers in journals and 200 conference papers and has supervised over 25 Ph. D. students. During the past ten years his research has focused on visual surveillance and general video analysis. He and his students have developed foundational methods for detection and tracking of people and vehicles in video, representation and recognition of human movements and activities, and mixed AI/signal processing models for event modeling and recognition. He is an Associate Editor of the International Journal of Computer Vision and an area editor for Computer Models for Image Processing: Image Understanding.

For more information please contact:
Gang Hua
Associate Professor
305 Lieb
Phone: 201.216.8073
E-mail: ghua@stevens.edu