The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Probabilistic Head Tracking Based on Cascaded Condensation Filtering

순차적 파티클 필터를 이용한 다중증거기반 얼굴추적

  • 김현우 (한독미디어대학원대학교 뉴미디어학부) ;
  • 기석철 ((주)만도 중앙연구소 산하 전자연구소)
  • Received : 2010.06.08
  • Accepted : 2010.08.06
  • Published : 2010.08.31
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Abstract

This paper presents a probabilistic head tracking method, mainly applicable to face recognition and human robot interaction, which can robustly track human head against various variations such as pose/scale change, illumination change, and background clutters. Compared to conventional particle filter based approaches, the proposed method can effectively track a human head by regularizing the sample space and sequentially weighting multiple visual cues, in the prediction and observation stages, respectively. Experimental results show the robustness of the proposed method, and it is worthy to be mentioned that some proposed probabilistic framework could be easily applied to other object tracking problems.

Keywords

References

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