PDF / BibTeX - ITSC 2014
A graph based people silhouette segmentation using combined probabilities extracted from appearance, shape template prior, and color distributions

Christophe CONIGLIO, Cyril MEURIE, Olivier LÉZORAY, Marion BERBINEAU



• BibTeX -

title={A Graph Based People Silhouette Segmentation Using Combined Probabilities Extracted from Appearance, Shape Template Prior, and Color Distributions},
author={Coniglio, Christophe and Meurie, Cyril and L{\'e}zoray, Olivier and Berbineau, Marion},
booktitle={Advanced Concepts for Intelligent Vision Systems},


In this paper, we present an approach for the segmentation of people silhouettes in images. Since in real-world images estimating pixel probabilities to belong to people or background is difficult, we propose to optimally combine several ones. A local window classifier based on SVMs with Histograms of Oriented Gradients features estimates probabilities from pixels’ appearance. A shape template prior is also computed over a set of training images. From these two probability maps, color distri- butions relying on color histograms and Gaussian Mixture Models are estimated and the associated probability maps are derived. All these probability maps are optimally combined into a single one with weight- ing coefficients determined by a genetic algorithm. This final probability map is used within a graph-cut to extract accurately the silhouette. Ex- perimental results are provided on both the INRIA Static Person Dataset and BOSS European project and show the benefit of the approach.

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