Visual Tracking of Self-Occluding Articulated Objects
James Matthew Rehg, Takeo Kanade · 1994
50559. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the o cial policies, either expressed or implied, of NASA or the U.S. government. Keywords: Model-Based Visual Tracking, Articulated and Nonrigid Object Motion, Occlusion, Human Motion Sensing, Human-Computer Interaction, Gesture Recognition 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 signi cant amounts of self-occlusion. These results extend the DigitEyes system for articulated tracking described in [22, 21] to handle self-occluding motions.