Rapid Forward Vehicle Detection Based on Deformable Part Model

This paper first introduce the general method of Deformable Part Model(DPM). In order to improve the speed of front vehicle detection, first, this paper propose a method to accelerate the calculation speed of HOG feature. Second,based on a series of important accelerating mechanisms, this paper mainly use Vector Quantization and K-means clustering algorithm to speed up the HOG feature computing speed, it use Vector Quantization to compress the HOG feature, which is convenient for fast scoring operation. Finally, test the method in different road scenes. Experimental results show that the method can improve the detection speed and meet the real-time requirement without sacrificing the detection precision.