关键词: 联合分割, 方向梯度直方图（HOG）特征, 超像素组合, 模范支持向量机（E-SVM）分类器, 分割传播

Abstract: As the problem of the unsatisfied clothing segmentation accuracy, a novel segmentation algorithm is proposed based on HOG（Histogram of Oriented Gradients） features and E-SVM（Exemplar Support Vector Machine） classifiers. The co-segmentation algorithm can be divided into three steps：Superpixel grouping, E-SVM classifier training, segmentation propagation, which uses an auxiliary dataset. Firstly, user input image is segmented in superpixel, which makes the images in auxiliary dataset into regions. Secondly, some regions are selected to a positive segmentation, which uses HOG information to train E-SVM classifiers. Finally, the cloth is segmented in user image by E-SVM classifiers and segmentation propagation. Experimental results show that the proposed algorithm can segment clothing images with high accuracy.

Key words: co-segmentation, Histogram of Oriented Gradients（HOG） feature, superpixel grouping, Exemplar Support Vector Machine（E-SVM） classifier, segmentation propagation