Online HOG Method in Pedestrian Tracking

Abstract

Object detection and tracking is one of the most important research topics in pattern recognition and the basis of many computer vision systems. Many accomplishments in this field have been achieved recently. Some specific objects, such as human face and vehicles, can already be detected in various applications. However, tracking objects with large variances in color, texture and local shape (such as pedestrians) is still a challenging topic in this field. To solve this problem, a pedestrian tracking scheme is proposed in this paper, including online training for pedestrian-detector. Simulation and analysis of the results shows that, the proposal method could deal with illumination change, pose change and occlusion problem and any combination thereof.