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Authors: Lixuan Yang 1 ; Helena Rodriguez 2 ; Michel Crucianu 3 and Marin Ferecatu 3

Affiliations: 1 Shopedia SAS and Conservatoire National des Arts et Métiers, France ; 2 Shopedia SAS, France ; 3 Conservatoire National des Arts et Métiers, France

Keyword(s): Dress Extraction, Clothing Extraction, Segmentation, SVM Classification, Active Contour.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Segmentation and Grouping

Abstract: In this work we propose a a dedicated object extractor for dress segmentation in fashion images by combining local information with a prior learning. First, a person detector is applied to localize sites in the image that are likely to contain the object. Then, an intra-image two-stage learning process is developed to roughly separate foreground pixels from the background. Finally, the object is finely segmented by employing an active contour algorithm that takes into account the previous segmentation and injects specific knowledge about local curvature in the energy function. The method is validated on a database of manually segmented images. We show examples of both successful segmentation and difficult cases. We quantitatively analyze each component and compare with the well-known GrabCut foreground extraction method.

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Paper citation in several formats:
Yang, L.; Rodriguez, H.; Crucianu, M. and Ferecatu, M. (2016). Classification-driven Active Contour for Dress Segmentation. In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP; ISBN 978-989-758-175-5; ISSN 2184-4321, SciTePress, pages 22-29. DOI: 10.5220/0005721000220029

@conference{visapp16,
author={Lixuan Yang. and Helena Rodriguez. and Michel Crucianu. and Marin Ferecatu.},
title={Classification-driven Active Contour for Dress Segmentation},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP},
year={2016},
pages={22-29},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005721000220029},
isbn={978-989-758-175-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP
TI - Classification-driven Active Contour for Dress Segmentation
SN - 978-989-758-175-5
IS - 2184-4321
AU - Yang, L.
AU - Rodriguez, H.
AU - Crucianu, M.
AU - Ferecatu, M.
PY - 2016
SP - 22
EP - 29
DO - 10.5220/0005721000220029
PB - SciTePress

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