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International Journal of Computer Vision
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Analyzing Video Sequences of Multiple Humans
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Real-time thresholding with Euler numbers
Pattern Recognition Letters
Real-Time Estimation of Human Body Posture from Monocular Thermal Images
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Moving Target Classification and Tracking from Real-time Video
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
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Digital Image Processing (3rd Edition)
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ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Local Properties of Binary Images in Two Dimensions
IEEE Transactions on Computers
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IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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IEEE Transactions on Image Processing
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IEEE Transactions on Circuits and Systems for Video Technology
Efficient moving object segmentation algorithm using background registration technique
IEEE Transactions on Circuits and Systems for Video Technology
Segmentation of human body parts using deformable triangulation
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PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part II
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part II
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This paper proposes a new method for vision-based human body posture estimation using body silhouette and skincolor information. A moving object segmentation algorithm is first proposed to distinguish the human body from the background using a sequence of images. This algorithm uses a fast Euler number computation technique to automatically determine the threshold of both frame and background differences. After segmentation, a sequence of image processing approaches then creates a complete silhouette of the human body. The objective of posture estimation is to locate five significant body points, including the head, tips of the feet, and tips of the hands. These significant points are first selected from convex points on a defined distance curve. A number of heuristic rules based on body shape characteristics are used to select the proper points among these convex candidates. These rules use features like the principal and minor axes of the human body, their interactions with the silhouette contour, the relative distances between convex points, and the curvature of convex points. An auxiliary skin-color feature is used when the silhouette shape features alone are not sufficient to estimate the significant points. Experimental results show that the proposed approach can efficiently and effectively locate the significant body points for most postures.