关键词: 目标跟踪, 抗遮挡, 特征重检, TLD算法, 双向匹配

Abstract:

Aiming at the occlusion problem of visual target tracking, this paper introduces feature redetection based on TLD（Tracking-Learning-Detection） algorithm to solve the misjudgments caused by similar appearance and background clustering of the target when occlusion occurs. A new method of anti-occlusion target tracking based on feature redetection（TLD-D） is proposed, which adopts the strategies of tracking, detection, learning and redetection. When occlusion occurrs, feature redetection is enabled to extract the two key frames of occlusion process, which are called the beginning of occlusion and the end of occlusion, and then SIFT feature is selected in feature redetection for bidirectional matching to calibrate the target to ensure that the re-calibrated target is the original tracking target, namely “redetection”. The experimental results show that compared with TLD algorithm and other classical tracking algorithms, the TLD-D algorithm has stronger anti-occlusion ability and robustness, and can track the target stably for a long time.

Key words: object tracking, anti-occlusion, feature redetection, Tracking-Learning-Detection（TLD） algorithm；bidirectional match