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This paper proposed a method of locating head-shoulder quickly and detecting with the fusion feature to solve the problems of pedestrian detection in video. It firstly selected the candidate pixel points in the foreground, for the pixel gradient direction of the top of the head had a fixed scope. Then it located the areas of human head-shoulder quickly by these points, which defined as the windows to be tested. Next, it extracted the HOG features and HSV features of the windows. Lastly, it trained the head-shoulder classifier by support vector machine (SVM). Experimental results show that based on the pixel gradient direction of the top of the head, the windows which contain head-shoulder can be located more quickly than the traditional method, sliding window, which improves the efficiency of the detection. Furthermore, the accuracy of detection is also improved by the fusion feature of HOG and HSV. Thus, the proposed method performs well and can help the subsequent analysis of the pedestrians. [ABSTRACT FROM AUTHOR]