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A Generative Model for Simultaneous Estimation of Human Body Shape and Pixel-Level Segmentation
Ingmar Rauschert and Robert T. Collins
Pennsylvania State University, University Park, 16802, PA, USAAbstract. This paper addresses pixel-level segmentation of a human body from a single image. The problem is formulated as a multi-region segmentation where the human body is constrained to be a collection of geometrically linked regions and the background is split into a small number of distinct zones. We solve this problem in a Bayesian framework for jointly estimating articulated body pose and the pixel-level segmentation of each body part. Using an image likelihood function that simultaneously generates and evaluates the image segmentation corresponding to a given pose, we robustly explore the posterior body shape distribution using a data-driven, coarse-to-fine Metropolis Hastings sampling scheme that includes a strongly data-driven proposal term.
LNCS 7576, p. 704 ff.
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© Springer-Verlag Berlin Heidelberg 2012