Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/16133
Título: Stripe based clothes segmentation
Autores/as: Lorenzo Navarro, José Javier 
Castrillón-Santana, Modesto 
Freire-Obregón, David 
Ramón Balmaseda, Enrique José 
Clasificación UNESCO: 120304 Inteligencia artificial
Palabras clave: Clothes segmentation
Fashion parsing
People segmentation
Fecha de publicación: 2015
Conferencia: 2015 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2015 
Resumen: 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.</p>
URI: http://hdl.handle.net/10553/16133
ISSN: 2330-7927
DOI: 10.1109/ICMEW.2015.7169791
Fuente: IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 29 june-3 july 2015, Turin, Italy [EISBN 978-1-4799-7079-7]
Colección:Actas de congresos
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