Human Object Detection by HoG, HoB, HoC and BO Features

摘要

Human object detection in image or video is always a challenge in computer vision which is hurdle in development of automatic cars and robots since machine till now is not able to categorize the object on its own. We have discussed the issues in human object detection algorithms in this paper and suggested a new feature extraction approach with SVM classifier. We have cascaded a new features set using four different features which provides color, edge, bar information along with minimization of false detection. These are HoG, HoC, HoB and BO respectively. With these features set we are able to get a good accuracy rate then previous work.