• Title/Summary/Keyword: 베이시안 확률모델

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A Study on the Gesture Recognition Based on the Particle Filter Using CONDENSATION Algorithm (CONDENSATION 알고리즘을 이용한 입자필터 기반 동작 인식 연구)

  • Lee, Yang-Weon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.3
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    • pp.584-591
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    • 2007
  • The recognition of human gestures in image sequences is an important and challenging problem that enables a host of human-computer interaction applications. This paper describes a gesture recognition algorithm based on the particle filters, namely CONDENSATION. The particle filter is more efficient than any other tracking algorithm because the tracking mechanism follows Bayesian estimation rule of conditional probability propagation. We used two models for the evaluation of particle filter and apply the MAILAB for the preprocessing of the image sequence. But we implement the particle filter using the C++ to get the high speed processing. In the experimental results, it is demonstrated that the proposed algorithm prove to be robust in the cluttered environment.