Pedestrian detection based on efficient fused lasso algorithm

The paper presents a new algorithm of pedestrian detection based on efficient fused lasso algorithm (EFLA) and analyses the sparse representation framework. The method considers the structure information of pedestrian image and makes it encoded into the sparse representation model to obtain good discrimination. The proposed algorithm makes use of EFLA to make features that they include the color, texture and shape features extracted from pedestrian image sparse, and detect pedestrian through support vector machine (SVM). The experimental results show that the proposed method has detection nature and better effect on massive data set as well as gives better robustness on the detection of difficult images.