Human Silhouette Extraction based on HMM

  • Authors:

  • San-Lung Zhao;Hsi-Jian Lee

  • Affiliations:

  • National Chiao-Tung University Hsinchu, Taiwan;Tzu-Chi University, Hualien, Taiwan

  • Venue:
  • ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper presents a system that can extract regions of a person from an image sequence. The system first detects foreground regions based on a background model. After foreground regions are extracted a human model is used to identify human regions. In the human model, we adopt a Hidden Markov Model (HMM) to model human silhouettes. To separate human and non-human regions, we represent non-human silhouettes by another HMM. The human silhouette model can extract incomplete human regions even when parts of the person are covered by background objects. Experimental results show the system proposed is very effective.