The proliferation of cheap sensors and increased processing power has made real-time acquisition and processing of video information more feasible. Real-time vision analysis tasks requiring object detection, tracking, and pose estimation can increasingly be performed efficiently on standard PCs. Smart cameras are being designed that enable on-camera applications to directly output compressed data or meta-event information instead of raw video. These advances, along with major breakthroughs in communication and the Internet, are making possible real-time video monitoring and augmented reality applications in a variety of application sectors such as Industrial Automation, Transportation, Automotive Systems, Security/Surveillance, and Communications.

This evening will highlight specific systems and applications, highlight technical challenges in their design and implementation, and discuss open research issues.

Dr. Visvanathan Ramesh obtained his doctoral degree from the Department of EE at the University of Washington, where he defended his Ph.D dissertation titled "Performance Characterization of Image Understanding Algorithms" in 1994. He has been actively involved in Image and Video Understanding research in low and mid level vision over the past 12 years and has published numerous publications in the topic. His primary objective is to build robust image and video analysis systems and to quantify robustness of video understanding algorithms.

Dr. Ramesh is currently head of the Real-time Vision and Modeling department at Siemens Corporate Research in Princeton NJ. At Siemens he has focused on the research and development of statistical methods for real-time video analysis functions such as object detection, tracking, and action recognition. He is a co-author of a paper on real-time tracking that received the best paper award in CVPR 2000. His broad research interests are Pattern Recognition, Computer Vision, AI and Biomedical Engineering.

A pre-meeting dinner with the speaker is held at 6 p.m. at the Rusty Scupper on Alexander Road in Princeton. If you would like to attend, please RSVP with an e-mail to princetonacm@acm.org.

Princeton ACM / IEEE Computer Society meeting are open to the public. Students and their parents are welcome. There is no admission charge, and refreshments are served.