Pedestrian Detection Based on Multi-scale HOG Features and Integral Images

摘要

In the light of slow-speed computation and poor performance in multi-scale detection of traditional HOG feature extraction algorithm, we put forward an improved pedestrian detection algorithm based on multi-scale HOG feature and integral image. On the basis of traditional HOG algorithm, firstly we introduce integral image and multi-scale HOG feature to reduce the feature dimension and avoid some repetitive computation. Next, we use INRIA data-set to train the SVM classifier and test it based on two different algorithms. It is concluded that the improved algorithm we have put forward enable the detection efficiency improvement with better recall, computation speed and robustness.