In this paper we propose a new content based approach for clothing image retrieval trying to mimic the human vision understanding not only based on naive manipulation of texture and color, but also combining some recent and advanced techniques like human pose estimation, super-pixel segmentation and cloth parsing. Moreover, we exploit metric learning to improve the image matching phase by proposing a new approach to learn a distance properly designed for the analyzed application. Specially in fashion sector our work seems very helpful in obtaining more accurate categorization and naturally desirable image retrieval from a large database of images of models dressing various types of style, pattern and fashion. In particular, a drastic improvement is observed when the metric learning strategy is introduced.

Advanced content based image retrieval for fashion / T.M. Dagnew, U. Castellani (LECTURE NOTES IN COMPUTER SCIENCE). - In: Image Analysis and Processing : ICIAP 2015 / [a cura di] V. Murino, E. Puppo. - [s.l] : Springer, 2015 Sep. - ISBN 9783319232300. - pp. 705-710 (( Intervento presentato al 18. convegno ICIAP tenutosi a Genova nel 2005 [10.1007/978-3-319-23231-7_63].

Advanced content based image retrieval for fashion

T.M. Dagnew
;
2015-09

Abstract

In this paper we propose a new content based approach for clothing image retrieval trying to mimic the human vision understanding not only based on naive manipulation of texture and color, but also combining some recent and advanced techniques like human pose estimation, super-pixel segmentation and cloth parsing. Moreover, we exploit metric learning to improve the image matching phase by proposing a new approach to learn a distance properly designed for the analyzed application. Specially in fashion sector our work seems very helpful in obtaining more accurate categorization and naturally desirable image retrieval from a large database of images of models dressing various types of style, pattern and fashion. In particular, a drastic improvement is observed when the metric learning strategy is introduced.
texture classification; parts
Settore INF/01 - Informatica
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/471033
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