Motivated by the availability of such rich data, we are exploring matching, reconstruction, and visualization algorithms that can work with very large, unorganized, and uncalibrated images sets, such as those found on the Internet. In this talk, I'll describe "Photo Tourism" (now being commercialized by Microsoft as "Photosynth"), an approach that creates immersive 3D experiences of scenes by reconstructing photographs on the Internet. I'll also describe work on multi-view stereo that reconstructs accurate 3D models from large collections of input views.
This is joint work with Noah Snavely, Rick Szeliski, Michael Goesele, Brian Curless, and Hugues Hoppe.
Bio: Steven Seitz is Short-Dooley Associate Professor in the Department of Computer Science and Engineering at the University of Washington. He received his B.A. in computer science and mathematics at the University of California, Berkeley in 1991 and his Ph.D. in computer sciences at the University of Wisconsin, Madison in 1997. Following his doctoral work, he spent one year visiting the Vision Technology Group at Microsoft Research, and subsequently two years as an Assistant Professor in the Robotics Institute at Carnegie Mellon University. He joined the faculty at the University of Washington in July 2000. He was twice awarded the David Marr Prize for the best paper at the International Conference of Computer Vision, and has received an NSF Career Award, an ONR Young Investigator Award, and an Alfred P. Sloan Fellowship. Professor Seitz is interested in problems in computer vision and computer graphics. His current research focuses on capturing the structure, appearance, and behavior of the real world from digital imagery.