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[YFC16] Classification-Driven Active Contour for Dress Segmentation
Conférence Internationale avec comité de lecture : 11th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP), February 2016, pp.22-29, Rome, Italie, (DOI: 10.5220/0005721000220029)Mots clés: Dress Extraction, Clothing Extraction, Segmentation, SVM Classification, Active Contour
Résumé:
In this work we propose a new approach for dress segmentation in fashion images by combining local information
with a learning prior to implement a dedicated object extractor. 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.
Equipe:
vertigo
BibTeX
| @inproceedings { | |||
| YFC16, | |||
| title | = | "{Classification-Driven Active Contour for Dress Segmentation}", | |
| author | = | " L. Yang and M. Ferecatu and M. Crucianu and H. Rodrigues ", | |
| booktitle | = | "{11th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP)}", | |
| year | = | 2016, | |
| month | = | "February", | |
| pages | = | "22-29", | |
| address | = | "Rome, Italie", | |
| doi | = | "10.5220/0005721000220029", | |
| } | |||
