"Video Acquisition, Processing and
Modeling of a Dynamic Scene"

Abstract: Computer vision technologies, as applied to video media, can do more than just convert images to nicer looking ones. They enable us to extract the information about the scene, such as motion and shape of objects contained in the image sequence. Using a few examples, I will talk about how a more interesting and captivating video of a dynamic scene can be acquired by using a large number of advanced real-time robotics cameras, and about how three-dimensional shape and object motion information can be effectively extracted by using the algebraic structure inherent in the image sequences.

In particular, I will describe the following three examples. Firstly, in 2001 we worked with CBS Sports to develop a multi-robot camera system that was used to broadcast the Super Bowl XXXV. The system, which CBS calls "EyeVision", produces a surrounding view of various interesting and controversial plays. Secondly, the Carnegie Mellon University's Virtualized Reality project has built a 3D room - a fully digital room that can capture events occurring in it by many (at this moment 50) surrounding video cameras. From those videos, we obtain a sequence of a complete 3D representation of the scene, named 4D representation. Finally, I will present a new method of segmenting an image sequence into meaningful layers or approximately planar surfaces in the scene, so that the perceptual problems of understanding the video will become more tractable. These examples demonstrate the combined use of robotics motion control, clean theoretical constraints embedded in the video, and real-time computing power.

Biography: Takeo Kanade received his Ph.D. in Electrical Engineering from Kyoto University, Japan, in 1974. After holding a faculty position at Kyoto University, he joined Carnegie Mellon University in 1980, where he is currently the U. A. Helen Whitaker University Professor of Computer Science and Robotics. He was the Director of the Robotics Institute of Carnegie Mellon from 1991 to 2001.

Dr. Kanade has worked in multiple areas of robotics: computer vision, manipulators, autonomous mobile robots, and sensors. He has been the principal investigator of more than a dozen major vision and robotics projects at Carnegie Mellon.

Dr. Kanade has been elected to the National Academy of Engineering. He is a Fellow of the IEEE, a Fellow of ACM, and a Founding Fellow of American Association for Artificial Intelligence. He received multiple awards, including the C & C Award, the Joseph Engelburger Award, the Marr Award, and the JARA Award.