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Iterative Human Segmentation from Detection Windows Using Contour Segment Analysis

Abstract : This paper presents a new algorithm for human segmentation in images. The human silhouette is estimated in positive windows that are already obtained with an existing efficient detection method. This accurate segmentation uses the data previously computed in the detection. First, a pre-segmentation step computes the likelihood of contour segments as being a part of a human silhouette. Then, a contour segment oriented graph is constructed from the shape continuity cue and the prior cue obtained by the pre-segmentation. Segmentation is so posed as the computation of the shortest-path cycle which corresponds to the human silhouette. Additionally, the process is achieved iteratively to eliminate irrelevant paths and to increase the segmentation performance. The approach is tested on a human image database and the segmentation performance is evaluated quantitatively.
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Contributor : Pascal Bertolino <>
Submitted on : Friday, March 8, 2013 - 3:39:27 PM
Last modification on : Thursday, November 19, 2020 - 1:01:03 PM
Long-term archiving on: : Sunday, June 9, 2013 - 9:20:07 AM


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  • HAL Id : hal-00798468, version 1



Cyrille Migniot, Pascal Bertolino, Jean-Marc Chassery. Iterative Human Segmentation from Detection Windows Using Contour Segment Analysis. VISAPP 2013 - 8th International Conference on Computer Vision Theory and Applications, Feb 2013, Barcelone, Spain. pp.CD. ⟨hal-00798468⟩



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