Human Movement Analysis

Abstract

The modeling and measurement of human movement are central to applications in visual surveillance and computer animation. The two most commonly studied approaches involve full 3D motion capture, on the one hand, and 2D “pose” tracking, on the other hand. Full 3D motion capture requires much higher resolution video than is typically available in surveillance. But modeling the types of everyday human movements of interest in surveillance – reaches, yanks, strikes, etc. - using dynamics of 2D silhouettes presents daunting computational challenges because of the high variability in the appearance of these movements. I describe an alternative approach based on the ballistic nature of common human movements. Our approach recognizes these ballistic movements independent of the movement's target-location and direction by modeling the ballistic dynamics. A video sequence is first segmented into ballistic subsequences without pose tracking, but instead based on global motion features of the body. The ballistic segments are then classified into strike and reach movements based on motion features. Each ballistic segment is further analyzed to compute qualitative labels for the movement's target-location and direction. Tests are presented with a set of reach and strike movement sequences. I will also describe the integration of this movement analysis system with appearance based object recognition, and show how the simultaneous recognition of movement and objects lead to higher classification rates for both.

Speaker Biography

Larry Davis (Ph. D. University of Maryland, 1976) is Professor and Chair of the Computer Science Department at the University of Maryland and Professor in the Institute for Advanced Computer Studies (UMIACS). He is a former Director of UMIACS and former Head of the Computer Vision Laboratory. Prof. Davis received his Ph. D. from the University of Maryland in 1975, and was an Assistant Professor of Computer Science at the University of Texas at Austin from 1977-1981. He returned to the University of Maryland as an Associate Professor in 1981. Prof. Davis has published over 200 articles on topics in computer vision and high performance computing. His current research focuses on visual surveillance, especially the modeling and recognition of human movement and activity. He is a Fellow of the IEEE and the IAPR and is currently serving on DARPA’s ISAT committee.