Visual Tracking of Self-Occluding Articulated Objects.
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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 31, 1994
- Accession Number
- ADA292894
Entities
People
- James R. Rehg
- Takeo Kanade
Organizations
- Carnegie Mellon University