@conference {13243,
	title = {Human body pose estimation using silhouette shape analysis},
	booktitle = {Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2003.},
	year = {2003},
	month = {2003/07//},
	pages = {263 - 270},
	abstract = {We describe a system for human body pose estimation from multiple views that is fast and completely automatic. The algorithm works in the presence of multiple people by decoupling the problems of pose estimation of different people. The pose is estimated based on a likelihood function that integrates information from multiple views and thus obtains a globally optimal solution. Other characteristics that make our method more general than previous work include: (1) no manual initialization; (2) no specification of the dimensions of the 3D structure; (3) no reliance on some learned poses or patterns of activity; (4) insensitivity to edges and clutter in the background and within the foreground. The algorithm has applications in surveillance and promising results have been obtained.},
	keywords = {3D, analysis;, body, classification;, clutter;, detection;, estimation;, extraction;, feature, function;, human, image, likelihood, multiple, object, parameter, parameters;, Pixel, pose, probability;, segmentation;, segmentations;, SHAPE, silhouette, structure;, surveillance;, views;},
	doi = {10.1109/AVSS.2003.1217930},
	author = {Mittal,A. and Liang Zhao and Davis, Larry S.}
}
