Integration of bottom-up/top-down approaches for 2D pose estimation using probabilistic Gaussian modelling

Kuo, Paul, Makris, Dimitrios and Nebel, Jean-Christophe (2011) Integration of bottom-up/top-down approaches for 2D pose estimation using probabilistic Gaussian modelling. Computer Vision and Image Understanding, 115(2), pp. 242-255. ISSN (print) 1077-3142

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Item Type: Article
Additional Information: This work was supported by Engineering and Physical Sciences Research Council (EPSRC) sponsored MEDUSA, and PROCESS projects (Grant No. EP/E001025/1 and EP/E033288 respectively)
Uncontrolled Keywords: human body pose estimation, stochastic clustering, gaussian mixture modelling, pattern classification, object recognition, confidence measure, ground truth, nonlinear dimensionality reduction, human-body configurations, human motion capture, 3d human motion, tracking people, segmentation, framework, parts
Research Area: Computer science and informatics
Faculty, School or Research Centre: Faculty of Computing, Information Systems and Mathematics (until 2011)
Faculty of Computing, Information Systems and Mathematics (until 2011) > Digital Imaging Research Centre (DIRC)
Depositing User: Automatic Import Agent
Date Deposited: 03 May 2011 14:28
Last Modified: 18 Nov 2011 16:42
URI: http://eprints.kingston.ac.uk/id/eprint/18469

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