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A Real-Time Model-Based Human Motion Tracking and Analysis for Human-Computer Interface Systems

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Abstract

This paper introduces a real-time model-based human motion tracking and analysis method for human computer interface (HCI). This method tracks and analyzes the human motion from two orthogonal views without using any markers. The motion parameters are estimated by pattern matching between the extracted human silhouette and the human model. First, the human silhouette is extracted and then the body definition parameters (BDPs) can be obtained. Second, the body animation parameters (BAPs) are estimated by a hierarchical tritree overlapping searching algorithm. To verify the performance of our method, we demonstrate different human posture sequences and use hidden Markov model (HMM) for posture recognition testing.

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Correspondence to Chung-Lin Huang.

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Huang, C., Chung, C. A Real-Time Model-Based Human Motion Tracking and Analysis for Human-Computer Interface Systems. EURASIP J. Adv. Signal Process. 2004, 616891 (2004) doi:10.1155/S1110865704401206

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Keywords and phrases

  • human computer interface system
  • real-time vision system
  • model-based human motion analysis
  • body definition parameters
  • body animation parameters