Tracking multiple humans in crowded environment

  • Authors:
  • Tao Zhao;Ram Nevatia

  • Affiliations:
  • Sarnoff Corporation, Princeton, NJ;IRIS, University of Southern California, Los Angeles, CA

  • Venue:
  • CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
  • Year:
  • 2004

Quantified Score

Hi-index 0.02

Visualization

Abstract

Tracking of humans in dynamic scenes has been an important topic of research. Most techniques, however, are limited to situations where humans appear isolated and occlusion is small. Typical methods rely on appearance models that must be acquired when the humans enter the scene and are not occluded. We present a method that can track humans in crowded environments, with significant and persistent occlusion by making use of human shape models in addition to camera models, the assumption that humanswalk on a plane and acquired appearance models. Experimental results and a quantitative evaluation are included.