A robust online tracking-detection co-training algorithm with applications to vehicle recognition

Abstract

Focusing on the vehicle tracking task in a video, we propose an Online Tracking-Detection Co-Training schema that integrates detecting and tracking results in a co-training style. The tracker follows the object from frame to frame and its trajectory is used in one of feature view in co-training process. The detector recognizes the patches including given object in current frame and corrects the tracker in broken frame. Our proposed model is verified through experiments on reality videos including some challenging situations.