Research of Pedestrian Tracking Based on HOG Feature and Haar Feature
Fan Yang · 2013
The detection and tracking of pedestrians in the real scene is one of the most concerned questions in the multi-people detection and tracking,especially under the condition that the occlusion,congestion and varied backgrounds of people have greatly challenged the research of multi-people detection and tracking.Haar and HOG features are applied in this research.The Haar-Like feature detector is used to detect the face when people come face to face with the camera,while the Part-Based Template is used to detect and track people in people’s sideway movement.After that,the maximum weight independent set is used to accomplish the relationship between the frames.The result of the detection and tracking from the ETH,TUD and local sample library attests that the hybrid algorithm has much higher accuracy and precision in detecting pedestrian’s front and side face.