A vision-based human identification method
In this paper, we proposed a vision-based human identification method for unconstrained images. The proposed method is composed of two parts: feature extraction and human identification classifier. After human detection, color and shape information is adopted for human identification. The dominant color feature is to measure the color information from some interesting points within the moving person. The directional swing distance is used to measure the change of body shape while walking. A SVM classifier with these features is trained to recognize persons. The experimental results demonstrate that the proposed system can achieve human identification well.