Accession Number : ADA292894

Title :   Visual Tracking of Self-Occluding Articulated Objects.

Corporate Author : CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF COMPUTER SCIENCE

Personal Author(s) : Rehg, James R. ; Kanade, Takeo

PDF Url : ADA292894

Report Date : 31 DEC 1994

Pagination or Media Count : 42

Abstract : Computer sensing of hand and limb motion is an important problem for applications in human-computer interaction, virtual reality, and athletic performance measurement. We describe a framework for local tracking of self-occluding motion, in which parts of the mechanism obstruct each others visibility to the camera. Our approach uses a kinematic model to predict occlusion and windowed templates to track partially occluded objects. We analyze our model of self-occlusion, discuss the implementation of our algorithm, and give experimental results for 3D hand tracking under significant amounts of self-occlusion. These results extend the DigitEyes system for articulated tracking described in 22, 21 to handle self-occluding motions.

Descriptors :   *MATHEMATICAL MODELS, *TRACKING, *VISUAL SURVEILLANCE, KINEMATICS, ALGORITHMS, DETECTION, MODELS, COMPUTERS, MOTION, VISIBILITY, CAMERAS, TEMPLATES, PARTS, MAN COMPUTER INTERFACE, EXTREMITIES.

Subject Categories : Cybernetics
      Military Intelligence
      Optical Detection and Detectors

Distribution Statement : APPROVED FOR PUBLIC RELEASE