• J.M. Rehg is with the Georgia Institute of Technology, 801 Atlantic Drive, Atlanta, GA 30332-0280. E-mail: firstname.lastname@example.org.
• V. Pavlovic is with the Department of Computer Science, Rutgers University, 110 Frelinghuysen Road, Piscataway, NJ 08854-8019.
• T.S. Huang is with the Department Information Department of Electrical & Computer Engineering, 2039 Beckman Institute for Advanced Science and Technology, 405 North Mathews, Urbana, IL 61801.
• W.T. Freeman is with the Massachusetts Institute of Technology (MIT) Artificial Intelligence Laboratory, 200 (545) Technology Square, MIT Building NE43, Cambridge, MA 02139. E-mail: email@example.com
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James M. Rehg received the PhD degree from Carnegie Mellon University in 1995. From 1996 to 2001, he led the computer vision research group at the Cambridge Research Laboratory of the Digital Equipment Corporation, which was acquired by Compaq Computer Corporation in 1998. In 2001, he joined the faculty of the College of Computing at the Georgia Institute of Technology, where he is currently an associate professor. His research interests include computer vision, machine learning, human-computer interaction, computer graphics, and distributed computing.
Vladimir Pavlovic received the PhD degree in electrical engineering from the University of Illinois at Urbana-Champaign in 1999. He is an assistant professor in the Computer Science Department at Rutgers University and an adjunct assistant professor in the Bioinformatics Program at Boston University. From 1999 to 2001, he was a member of the research staff at the Cambridge Research Laboratory, Cambridge, Massachusetts. His research interests include statistical modeling of time-series, statistical computer vision, machine learning, and bioinformatics.
Thomas S. Huang received the BS degree in electrical engineering from the National Taiwan University, Taipei, Taiwan, China, the MS, and ScD degrees in electrical engineering from the Massachusetts Institute of Technology (MIT), Cambridge. From 1963 to 1973, he was on the faculty of the Department of Electrical Engineering at MIT. From 1973 to 1980, he was on the faculty of the School of Electrical Engineering and director of its Laboratory for Information and Signal Processing at Purdue University. In 1980, he joined the University of Illinois at Urbana-Champaign, where he is now William L. Everitt Distinguished Professor of Electrical and Computer Engineering, a research professor at the Coordinated Science Laboratory, the head of the Image Formation and Processing Group at the Beckman Institute for Advanced Science and Technology, and a cochair of the Institute's major research theme-Human Computer Intelligent Interaction. He has published 14 books and more than 500 papers in network theory, digital filtering, image processing, and computer vision. He is a member of the National Academy of Engineering, a foreign member of the Chinese Academies of Engineering and Sciences, and a fellow of the International Association of Pattern Recognition, IEEE, and the Optical Society of American. He has received a Guggenheim Fellowship. He was awarded the IEEE Third Millennium Medal in 2000. Also in 2000, he received the Honda Lifetime Achievement Award for "contributions to motion analysis." In 2001, he received the IEEE Jack S. Kilby Medal. In 2002, he received the King-Sun Fu Prize, International Association of Pattern Recognition; and the Pan Wen-Yuan Outstanding Research Award.
William T. Freeman studied computer vision for the PhD degree in 1992 from the Massachussetts Institute of Technology (MIT). He is an associate professor of electrical engineering and computer science at the Artificial Intelligence Laboratory at MIT, joining the faculty in 2001. From 1992 to 2001, he worked at Mitsubishi Electric Research Labs (MERL), in Cambridge, Massachusetts, most recently, as a senior research scientist and associate director. His current research interests include machine learning applied to computer vision, Bayesian models of visual perception, and interactive applications of computer vision. In 1997, he received the Outstanding Paper prize at the Conference on Computer Vision and Pattern Recognition for work on applying bilinear models to "separating style and content." Previous research topics include steerable filters and pyramids, the generic viewpoint assumption, color constancy, and computer vision for computer games.