Stripe based clothes segmentation

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.

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“…In a plenary meeting scenario, people normally wear the same clothes during the whole session so this visual cue can give us valuable information about the speaker. In order to characterize the clothes, color information is used because it has been shown to give good results in clothes segmentation problem [34]. Therefore, the descriptor chosen for the clothes is the 2D…”