CONTOUR SEGMENT ANALYSIS FOR HUMAN SILHOUETTE PRE-SEGMENTATION

Cyrille Migniot, Pascal Bertolino, Jean-Marc Chassery

2010

Abstract

Human detection and segmentation is a challenging task owing to variations in human pose and clothing. The union of Histograms of Oriented Gradients based descriptors and of a Support Vector Machine classifier is a classic and efficient method for human detection in the images. Conversely, as often in detection, accurate segmentation of these persons is not performed. Many applications however need it. This paper tackles the problem of giving rise to information that will guide the final segmentation step. It presents a method which uses the union mention above to relate to each contour segment a likelihood degree of being part of a human silhouette. Thus, data previously computed in detection are used in the pre-segmentation. A human silhouette database was ceated for learning.

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Paper Citation


in Harvard Style

Migniot C., Bertolino P. and Chassery J. (2010). CONTOUR SEGMENT ANALYSIS FOR HUMAN SILHOUETTE PRE-SEGMENTATION . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-029-0, pages 74-80. DOI: 10.5220/0002845300740080

in Bibtex Style

@conference{visapp10,
author={Cyrille Migniot and Pascal Bertolino and Jean-Marc Chassery},
title={CONTOUR SEGMENT ANALYSIS FOR HUMAN SILHOUETTE PRE-SEGMENTATION},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={74-80},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002845300740080},
isbn={978-989-674-029-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)
TI - CONTOUR SEGMENT ANALYSIS FOR HUMAN SILHOUETTE PRE-SEGMENTATION
SN - 978-989-674-029-0
AU - Migniot C.
AU - Bertolino P.
AU - Chassery J.
PY - 2010
SP - 74
EP - 80
DO - 10.5220/0002845300740080