Learning in Graphics and Vision

Workshop Organizers

Radek Grzeszczuk Intel Labs Intel Corporation 2200 Mission College Blvd. Mailstop: SC12-303 Santa Clara, CA, 95054 email: radek.grzeszczuk[at]intel.com phone: 408-653-9470

Radek Grzeszczuk has been a member of the Senior Research Staff at Intel's Microprocessor Research Labs since 1997. He received his Ph.D. degree (1998) and his MSc degree (1994) in Computer Science from University of Toronto. His research interests span computer graphics, computer vision and computational learning. His Ph.D. thesis was on using neural networks for fast emulation and control of physics-based models. His recent work focuses on efficient representation and visualization of complex shape and reflectance properties of objects, and on image-based rendering and modeling using programmable graphics hardware. He is on the Editorial Board of ACM Transactions on Graphics.

Aaron Hertzmann University of Toronto University of Toronto Dept. Computer Science 10 King's College Rd, Rm 3302 Toronto M5S 3G4 CANADA email: hertzman[at]dgp.toronto.edu phone: 416-946-8497

Aaron Hertzmann received his BA in Computer Science and Art & Art History from Rice University in 1996, and his MS and Ph.D. in Computer Science from New York University, in 1998 and 2001, respectively. He has worked at University of Washington, Microsoft Research, MERL, Interval and NEC. He is serving/has served on the papers committees for SIGGRAPH 2003-2004, EGSR 2003, CVPR 2003, and NPAR 2002, and is co-chairing NPAR 2004. Aaron has co-authored six papers at SIGGRAPH, five at vision conferences (ECCV, CVPR, and ICCV), and one at NIPS. His research concerns the intersections of computer graphics, computer vision, and machine learning, including applications to character animation, shape reconstruction, texture synthesis, image processing, and non-photorealistic rendering. He is presenting a tutorial course on Bayesian learning at SIGGRAPH 2004; it is the first machine learning course to be presented in a graphics venue.

Confirmed Speakers

Michael J. Black Brown University	Michael Black received his Ph.D. in computer science from Yale University in 1992. He has been a visiting researcher at the NASA Ames Research Center and an Assistant Professor in the Dept. of Computer Science at the University of Toronto. In 1993 Prof. Black joined the Xerox Palo Alto Research Center where he managed the Image Understanding area and later founded the Digital Video Analysis group. In 2000, Prof. Black joined the faculty of Brown University where he holds the position of Professor of Computer Science. At CVPR'91 he received the IEEE Computer Society Outstanding Paper Award for his work with P. Anandan on robust optical flow estimation. In 1999 his paper with David Fleet on probabilistic detection and tracking of motion discontinuities received Honorable Mention for the Marr Prize. Prof. Black's research interests include optical flow estimation, human motion analysis, robust statistics, and brain-computer interfaces.
David A. Forsyth University of California, Berkeley	David Forsyth holds a BSc and an MSc in Electrical Engineering from the University of the Witwatersrand, Johannesburg , and an MA and D.Phil from Oxford University. He is currently a full professor at U.C. Berkeley. He has published over 90 papers on computer vision, computer graphics and machine learning. He served as program co-chair for IEEE Computer Vision and Pattern Recognition in 2000, and is a regular member of the program committee of all major international conferences on computer vision. He has received best paper awards at the International Conference on Computer Vision and at the European Conference on Computer Vision. His recent textbook, "Computer Vision: A Modern Approach" (joint with J. Ponce and published by Prentice Hall) is now widely adopted as a course text (adoptions include MIT, U. Wisconsin-Madison, UIUC, Georgia Tech and U.C. Berkeley ).
William T. Freeman Massachusetts Institute of Technology	Bill Freeman has been an Associate Professor at MIT since 2001. Before that, he developed electronic cameras and printers at Polaroid for 6 years, was a Foreign Expert at the Taiyuan University of Technology (China) for a year, and a researcher at Mitsubishi Electric Research Labs (MERL) for 9 years. 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, learning low-level vision, and computer vision for computer games. His current research interests are at the intersection of machine learning, computer vision, and computer graphics. Hobbies include kite aerial photography.
Nebojsa Jojic Microsoft Research	Nebojsa Jojic has been with Microsoft Research since. He earned his PhD at the University of Illinois at Urbana-Champaign in 2001 where he received a Microsoft Fellowship in 1999 and a Robert T. Chien excellence in research award in 2000. Dr. Jojic also spent a semester at the University of Illinois at Chicago and consulted for the Hong Kong University of Science and Technology. He has published over 40 papers in the areas of computer vision, machine learning, signal processing, and computer graphics.
Hanspeter Pfister Mitsubishi Electric Research Laboratories	Hanspeter Pfister is Associate Director and Senior Research Scientist at MERL - Mitsubishi Electric Research Laboratories - in Cambridge, MA. He is the chief architect of VolumePro, Mitsubishi Electric's real-time volume rendering hardware for PCs. His research interests include computer graphics, scientific visualization, and computer architecture. His work spans a range of topics, including point-based graphics, 3D photography, 3D face recognition, volume graphics, and computer graphics hardware. Hanspeter Pfister received his Ph.D. in Computer Science in 1996 from the State University of New York at Stony Brook. He received his M.S. in Electrical Engineering from the Swiss Federal Institute of Technology (ETH) Zurich, Switzerland, in 1991. Dr. Pfister has taught courses at major graphics conferences including SIGGRAPH, IEEE Visualization, and Eurographics. He has been teaching introductory and advanced graphics courses at the Harvard Extension School since 1999. He is Associate Editor of the IEEE Transactions on Visualization and Computer Graphics (TVCG), chair of the IEEE Technical Committee on Visualization and Computer Graphics (TCVG), and has served as a member of international program committees of major graphics conferences. Dr. Pfister was the general chair of the IEEE Visualization 2002/03 conference. He is senior member of the IEEE, and member of ACM, ACM SIGGRAPH, the IEEE Computer Society, and the Eurographics Association.
Zoran Popović University of Washington	Zoran Popović is an Associate Professor in computer science at University of Washington. He received a Sc.B. with Honors from Brown University, and M.S. and Ph.D in Computer Science from Carnegie Mellon University. He has held research positions at Sun Microsystems and Justsystem Research Center and University of California at Berkeley. Zoran's research interests lie in computer animation, primarily in physically based modeling, high-fidelity human modeling, and control of realistic natural motion. His contributions to the field of computer graphics have been recently recognized by a number of awards including the NSF CAREER Award, Alfred P. Sloan Fellowship and ACM SIGGRAPH Significant New Researcher Award.
Deva Ramanan University of California, Berkeley	Deva Ramanan received a Bachelors of Computer Engineering (BCE) degree with distinction, summa cum laude, from the University of Delaware in 2000. He is a PhD student at the University of California at Berkeley in the electrical engineering and computer science (EECS) department, where his research has been supported by a UC MICRO fellowship and by a US National Science Foundation Graduate research fellowship. His research interests include computer vision, computer graphics, and machine learning.
Demetri Terzopoulos New York University and University of Toronto	Demetri Terzopoulos holds the Lucy and Henry Moses Professorship in Science at New York University and is Professor of Computer Science and Mathematics at NYU's Courant Institute. He is also Professor of Computer Science and Professor of Electrical and Computer Engineering at the University of Toronto. He graduated from McGill University and received the PhD degree in EECS from MIT in 1984. Prior to becoming an academic in 1989, he was a program leader in Schlumberger corporate research labs in California and Texas. His published work comprises hundreds of research papers and several volumes, primarily in computer graphics and computer vision, as well as in medical imaging, computer-aided design, artificial intelligence, and artificial life. He has given hundreds of invited talks around the world, including numerous distinguished lectures and keynote addresses. A Fellow of the IEEE, he has been a Killam Fellow of the Canada Council for the Arts, a Steacie Fellow of the Natural Sciences and Engineering Research Council of Canada, and a Fellow of the Canadian Institute for Advanced Research. In Fall 2004 he will be a Senior Fellow at UCLA's Institute for Pure and Applied Mathematics (IPAM). His many honors include computer graphics awards from Ars Electronica, NICOGRAPH, Computers and Graphics, and the International Digital Media Foundation and computer vision awards from the IEEE, the Canadian Image Processing & Pattern Recognition Society, the American Association for Artificial Intelligence, and the International Medical Informatics Association. Terzopoulos was program co-chair of the 1998 IEEE Conference on Computer Vision and Pattern Recognition and is program co-chair of Pacific Graphics 2004. He is a founding editorial board member of four journals spanning the vision, graphics, and medical imaging fields.
Sebastian Thrun Stanford University	Professor Sebastian Thrun is the Director of the Stanford AI Lab, home to more than 120 AI researchers at Stanford University. Thrun has pioneered the area of probabilistic robotics. He also pursues research on machine learning, AI, and multi-agent systems. He has won numerous best paper awards, an endowed chair, and has been a frequent keynote speaker at international conferences in AI and robotics. Thrun has published over 250 papers, including seven books and edited volumes, and he serves on the editorial board of a number of journals in robotics and AI. He was general chair of the 2003 NIPS conference, program chair of NIPS 2002, and the general chair of the 1998 CONALD conference. Thrun joined Stanford University in 2003, after having been on the faculty of Carnegie Mellon University for eight years.