Detecting pedestrian using motion information and part detectors

Abstract

A pedestrian detection method based on motion information and part detectors is proposed in this paper used for handling partial occlusions of pedestrian in video. Extracting motion areas in the video image by fast frame difference image Gaussian mixture model as the candidate region of the pedestrian firstly; Then the part detectors including head, head-left should, head-right should, torso and so on, which have trained by the liner SVM combined with the HOG features pyramid were used to scanning detect in each candidate region individually. Finally, the Max Margin Hough Transform is used to verify the detection result. Experiments on databases and the video shoot by us show that our method has high performance in detecting pedestrians with partial occlusion. © 2013 Springer-Verlag.