Abstract: On the basis of histogram of oriented gradient and support vector machine(HOG-SVM)algorithm,this paper proposed an improved algorithm for combination classifiers.Firstly,This algorithm uses multi-scale sliding windows to extract the HOG features and trains SVM separately.Then,the trained SVM which is formed to a new classifier in series or parallel is used to detect pedestrian.In order to solve the problem that the target area is overlapped when features are extracted in multi-scale sliding windows,the non-maximum suppression (NMS)algorithm is used to fuse the rectangles and to get exact candidate region.Experiments show that combined SVM classifiers can effectively reduce the false detection rate and missed rate.

Key words: Pedestrian detection,Histogram of oriented gradient(HOG),Support vector machine(SVM),Non-maximum suppression(NMS),Combination classifiers