DocumentCode :
3330688
Title :
Stripe based clothes segmentation
Author :
Lorenzo-Navarro, Javier ; Castrillon-Santana, Modesto ; Freire-Obregon, David ; Ramon-Balmaseda, Enrique
Author_Institution :
Inst. Univ. SIANI, Univ. de Las Palmas de Gran Canaria, Las Palmas, Spain
fYear :
2015
fDate :
June 29 2015-July 3 2015
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, a clothes segmentation method for fashion parsing is described. This method does not rely in a previous pose estimation but people segmentation. Therefore, novel and classic segmentation techniques have been considered and improved in order to achieve accurate people segmentation. Unlike other methods described in the literature, the output is the bounding box and the predominant color of the different clothes and not a pixel level segmentation. The proposal is based on dividing the person area into an initial fixed number of stripes, that are later fused according to similar color distribution. To assess the quality of the proposed method the experiments are carried out with the Fashionista dataset that is widely used in the fashion parsing community.
Keywords :
clothing industry; image colour analysis; image segmentation; production engineering computing; Fashionista dataset; bounding box; fashion parsing; fashion parsing community; people segmentation; pixel level segmentation; predominant color; similar color distribution; stripe based clothes segmentation; Accuracy; Clothing; Estimation; Image color analysis; Image segmentation; Indexes; Proposals; Clothes segmentation; fashion parsing; people segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia & Expo Workshops (ICMEW), 2015 IEEE International Conference on
Conference_Location :
Turin
Type :
conf
DOI :
10.1109/ICMEW.2015.7169791
Filename :
7169791
Link To Document :
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