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.

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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

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Cognitive Systems Engineering
  • Composite Images
  • Computational Science
  • Computations
  • Computer Graphics
  • Computer Science
  • Computer Vision
  • Computers
  • Graphics
  • Human-Computer Interaction
  • Human-Machine Interaction
  • Image Segmentation
  • Recognition
  • Relative Motion
  • User Interface
  • Virtual Reality

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Vision.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.