Person re-identification via region-of-interest based features

Person re-identification is still a challenging task due to large visual appearance variations caused by illumination, background, viewpoints and poses in multi-camera surveillance. To address these challenges, many methods have been proposed. In this paper, we present an efficient method, called Region-of-Interest based Features (ROIF), via combining textural and chromatic features. It consists of two main phases - region-of-interest exploration from image and features extraction from ROI. Experimental results on the database VIPeR show that our method can yield promising accuracy with a quite cheap time cost.