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J. Shotton, el al.,“Real-time Human Pose Recognition in Parts from Single Depth Images,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 20-25 June, 2011, pp. 1297-1304.

has been cited by the following article:

• TITLE: Human Body Tracking and Pose Estimation Using Modified Camshift Algorithm

  AUTHORS: Seung-Jun Hwang, Jae-Hong Min, In-Gyu Kim, Seung-Jae Park, Gwang-Pyo Ahn, Joong-Hwan Baek

  KEYWORDS: Body Tracking; CAMShift; Pose Estimation; Kalman Filter; Weighted Search Windows

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.6 No.5B, October 12, 2013

  ABSTRACT: In this paper, we propose multiple CAMShift Algorithm based on Kalman filter and weighted search windows that extracts skin color area and tracks several human body parts for real-time human tracking system. The CAMShift Algorithm we propose searches the skin color region by detecting the skin color area from background model. Kalman filter stabilizes the floated search area of CAMShift Algorithm. Each occlusion areas are avoided by using weighted window of non-search areas and main-search area. And shadows are eliminated from background model and intensity of shadow. The proposed modified Camshaft algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.