Optimization Algorithm and Implementation of Pedestrian Detection

摘要

Pedestrian detection is widely used in automotive assisting driving system. The algorithm based on Histograms of Oriented Gradient (HOG for short) feature is the main one in the current pedestrian detection. This paper uses tri-linear interpolation method to extract the image HOG features, and gives the optimization algorithm based on look-up table to reduce the amount of calculation in extracting HOG feature. And then classifies them by RBF and linear SVM to explore its speed and accuracy. At the end of the paper, an effective method is given to merge windows that contain detected pedestrians. Experiments on INRIA and MIT databases show that the detecting accuracy and speed of this method is relatively high.