HOG pedestrian detection based on edge symmetry and trilinear interpolation
Dandan Wang, Tongwei Lu, Yandou Zhang · 2018
In computer vision, pedestrian detection is a key problem. In this paper, we propose to speed up the HOG+SVM algorithm without sacrificing the classification accuracy. In order to eliminate the effects of aliasing phenomenon that products in the process of HOG extraction, we used trilinear interpolation to extract feature. This paper proposed HOG pedestrian detection method based on edge symmetry. In these experiments, we used INRIA dataset. Traditional HOG pedestrian detection is presence of slow detection speed and low detection rate. Experiments show that using trilinear interpolation and edge symmetry not only can improve the detection effect, but also can improve the detection rate.