January 26, 2001
Real-time vision is a potentially rich source of feedback for dynamic interaction with the physical world. Today¹s commercial processors are now easily powerful enough to realize interesting and useful systems based on ³dynamic² vision. This talk will survey some of our work on developing effective, general-purpose algorithms for dynamic vision, and will describe our recent work on software abstractions for vision-based systems.
Professor Gregory D. Hager received a B.A. degree in computer science and mathematics from Luther College in 1983, and his M.S. and Ph.D. in computer science from the University of Pennsylvania in 1985 and 1988, respectively. From 1988 to 1990 he was a Fullbright junior research fellow at the University of Karlsruhe and the Fraunhofer Institute IITB in Karlsruhe Germany. He then joined the computer science department at Yale University where he remained until 1999. Currently, he is a Professor of Computer Science at The Johns Hopkins University and a faculty member of the Center for Computer Integrated Surgical Systems and Technology. Professor Hager has published more than 100 articles and books in the area of vision and robotics. His current research interests include dynamic vision, Vision-based control, human-machine interaction and sensor data fusion.