Clothing Style Recognition and Design by Using Feature Representation and Collaboration Learning

Abstract

In order to recognize the clothing style, this paper establishes a standard clothing style library. The images of clothing style are provided and annotated by fashion design experts. The clothing style image is represented as a set of line segments that is obtained by detecting the lines and corners consisting of the edge feature points in the image. Then, the authors extract the features of the line segment set and use the extracted features to establish clothing style matching rules to make the system automatically produce the matching and recognizing criteria for the clothing style images. When inputting an image of a person wearing clothes, they first find the position of the person through skin color detection and then locate the clothing. The clothing region is segmented by seed growth algorithm. The features of the segmentation are compared with clothing style matching rules to determine the style. The experimental results show that the recognition rate of clothing style can reach more than 92% for the standard clothing images and more than 91% for real clothing images.