In this paper we propose a color-based approach for skin detection and interest garment selection aimed at an automatic segmentation of pieces of clothing. For both purposes, the color description is extracted by an iterative energy minimization approach and an automatic initialization strategy is proposed by learning geometric constraints and shape cues. Experiments confirms the good performance of this technique both in the context of skin removal and in the context of classification of garments.

Learning Non-Target Items for Interesting Clothes Segmentation in Fashion Images / Grana, Costantino; Calderara, Simone; Borghesani, Daniele; Cucchiara, Rita. - ELETTRONICO. - (2012), pp. 3317-3320. (Intervento presentato al convegno 21st International Conference on Pattern Recognition (ICPR 2012) tenutosi a Tsukuba Science City, Japan nel Nov 11-15).

Learning Non-Target Items for Interesting Clothes Segmentation in Fashion Images

GRANA, Costantino;CALDERARA, Simone;BORGHESANI, Daniele;CUCCHIARA, Rita
2012

Abstract

In this paper we propose a color-based approach for skin detection and interest garment selection aimed at an automatic segmentation of pieces of clothing. For both purposes, the color description is extracted by an iterative energy minimization approach and an automatic initialization strategy is proposed by learning geometric constraints and shape cues. Experiments confirms the good performance of this technique both in the context of skin removal and in the context of classification of garments.
2012
21st International Conference on Pattern Recognition (ICPR 2012)
Tsukuba Science City, Japan
Nov 11-15
3317
3320
Grana, Costantino; Calderara, Simone; Borghesani, Daniele; Cucchiara, Rita
Learning Non-Target Items for Interesting Clothes Segmentation in Fashion Images / Grana, Costantino; Calderara, Simone; Borghesani, Daniele; Cucchiara, Rita. - ELETTRONICO. - (2012), pp. 3317-3320. (Intervento presentato al convegno 21st International Conference on Pattern Recognition (ICPR 2012) tenutosi a Tsukuba Science City, Japan nel Nov 11-15).
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/766090
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 2
social impact