A complete system for garment segmentation and color classification
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- 作者：Marco Manfredi (1)
Costantino Grana (1)
Simone Calderara (1)
Rita Cucchiara (1) - 关键词：Image retrieval ; Segmentation ; Color clustering ; Graph ; cut
- 刊名：Machine Vision and Applications
- 出版年：2014
- 出版时间：May 2014
- 年：2014
- 卷：25
- 期：4
- 页码：955-969
- 全文大小：2,354 KB
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Costantino Grana (1)
Simone Calderara (1)
Rita Cucchiara (1)
1. Università degli Studi di Modena e Reggio Emilia, via Vignolese 905/b, Modena, Italy - ISSN：1432-1769
文摘
In this paper, we propose a general approach for automatic segmentation, color-based retrieval and classification of garments in fashion store databases, exploiting shape and color information. The garment segmentation is automatically initialized by learning geometric constraints and shape cues, then it is performed by modeling both skin and accessory colors with Gaussian Mixture Models. For color similarity retrieval and classification, to adapt the color description to the users-perception and the company marketing directives, a color histogram with an optimized binning strategy, learned on the given color classes, is introduced and combined with HOG features for garment classification. Experiments validating the proposed strategy, and a free-to-use dataset publicly available for scientific purposes, are finally detailed.