Event Location: NSH 3305
Bio: Yaser Sheikh is an Assistant Research Professor at the Robotics Institute and Adjunct Professor at the Department of Mechnical Engineering at Carnegie Mellon University. His research is in understanding dynamic scenes through computer vision, including human activity analysis, dynamic scene reconstruction, mobile camera networks, and nonrigid motion estimation. He obtained his doctoral degree from the University of Central Florida in 2006 and is a recipient of the Hillman award for excellence in computer science research.

Abstract: Most video analysis systems assume staring cameras that continuously view the same scene from the same point of view. Increasingly, as cameras and computers are becoming smaller and cheaper, freely moving cameras are emerging as a primary platform for computer vision research. Background subtraction algorithms, a mainstay in most computer vision systems, define the background as parts of a scene
that are at rest. Traditionally, these algorithms assume a stationary camera, and identify moving objects by detecting areas in a video that change over time. In this talk, I will present ideas to extend the concept of ‘subtracting’ areas at rest to apply to video captured from a freely moving camera. We do not assume that the background is well-approximated by a plane or that the camera center remains
stationary during motion. The method operates entirely using 2D image measurements without requiring an explicit 3D reconstruction of the scene.