Instructors: Ron Fedkiw (Stanford University), Stanley Osher (UCLA), and Guillermo Sapiro (University of Minnesota).
Duration: 3.5 hours
This short course will introduce the audience to the basic concepts of level-set methods and partial differential equations and their use to develop state of the art algorithms in computer vision, image processing, and computer graphics. We will present the basic derivation of level-sets techniques, fundamental numerical analysis and computational approaches, and cover topics such as image segmentation and classification, image segmentation, image in-painting, image decomposition, and modeling of natural phenomena. The course will be based on the books of instructors and new material developed by leaders in the area.
Ron Fedkiw received his Ph.D. in Mathematics from UCLA in 1996 and id postdoctoral studies both at UCLA in Mathematics and at Caltech in Aeronautics before joining the Stanford Computer Science Department. He was awarded a Packard Foundation Fellowship, a Presidential Early Career Award for Scientists and Engineers (PECASE), a Sloan Research Fellowship, an Office of Naval Research Young Investigator Program Award (ONR YIP), a Robert N. Noyce Family Faculty Scholarship, two distinguished teaching awards, etc. Currently he is on the editorial board of the Journal of Scientific Computing and the IEEE Transactions on Visualization and Computer Graphics, and participates in the reviewing process of a number of journals and funding agencies. He has published approximately 40 research papers in computational physics, computer graphics and vision, as well as a new book on level set methods. For the past two years, he has been a consultant with Industrial Light + Magic.
Stanley Osher received his Ph.D. from New York University, 1966, M.S from New York University, 1964, and B.S. from Brooklyn College, 1962. He is currently a Professor at UCLA, Department of Mathematics and Director of Special Projects, Institute for Pure and Applied Mathematics, UCLA His honors include Japan Society of Mechanical Engineers Computational Mechanics Award, (2002) Invited Speaker, International Congress of Mathematicians, 1994, NASA Public Service Group Achievement Award, 1992, US-Israel BSF Fellow, 1986, SERC Fellowship (England), 1982, Alfred P. Sloan Fellow, 1972-1974, and Fulbright Fellow, 1971. His work has been cited frequently by the national and international media, most recently in Science News, v155, April 1999, ``Computing at the Edge", and Die Zeit, v16, Sept. 1999, ``Flutwellen aus dem Computer" From 1988-1995 he was Co-Founder, Co-CEO of Cognitech, Inc, CA. This company has been recognized professionally and by the media for its innovative and successful nonlinear partial differential based approach to image and video processing. From 1998-present, Founder, CEO of Level Set Systems, Inc., Pacific Palisades, CA. His research consists of developing innovative numerical methods to solve partial differential equations, especially those whose solutions have steep gradients, analysis of these algorithms and the underlying P.D.E.'s and applications to various areas of Engineering, Physics and recently, image processing. He is a pioneer in numerical methods for shock capturing and one of the inventors of the famous level-sets methods. He wrote some of the first papers on PDE's based image processing and developed or co-developed some of the fundamental numerical methods used in image processing and computer vision. He was the recipient of the ICIAM Pioneer Prize (2003) and the Japan Society of Mechanical Engineers Computational Mechanics Award (2002). In addition, he is an ISI Original Highly Cited Researcher.
Guillermo Sapiro was born in Montevideo, Uruguay, on April 3, 1966. He received his B.Sc. (summa cum laude), M.Sc., and Ph.D. from the Department of Electrical Engineering at the Technion, Israel Institute of Technology, in 1989, 1991, and 1993 respectively. After post-doctoral research at MIT, Dr. Sapiro became Member of Technical Staff at the research facilities of HP Labs in Palo Alto, California. He is currently with the Department of Electrical and Computer Engineering at the University of Minnesota. G. Sapiro works on differential geometry and geometric partial differential equations, both in theory and applications in computer vision, computer graphics, medical imaging, and image analysis. He recently co-edited a special issue of IEEE Image Processing in this topic and a second one in the Journal of Visual Communication and Image Representation. He has authored and co-authored numerous papers in this area and has written a book published by Cambridge University Press, January 2001. G. Sapiro was awarded the Gutwirth Scholarship for Special Excellence in Graduate Studies in 1991, the Ollendorff Fellowship for Excellence in Vision and Image Understanding Work in 1992, the Rothschild Fellowship for Post-Doctoral Studies in 1993, the Office of Naval Research Young Investigator Award in 1998, the Presidential Early Career Awards for Scientist and Engineers (PECASE) in 1988, and the National Science Foundation Career Award in 1999. G. Sapiro is a member of IEEE and SIAM.