Research On Fast Multiple-Object Tracking Algorithm Based On TLD

Due to the large detection area in traditional TLD object tracking algorithm the time of detection processing takes too long and the result of similar object tracking is not satisfactory. Another problem in TLD model is that it can't hand multiple-object tracking in every single video frame. Therefore in this paper, an efficient approach (TLD-DO) is proposed for object tracking in which the surveyed areas can automatic adjustment according to the object's velocity of movement. It also proposes a multiple-object tracking optimization algorithm based on TLD-DO in this paper. In order to accelerate the process speed of TLD algorithm without reducing tracking precision, a novel algorithm named DKF with optimal surveyed area which can reduce the detection range of TLD detector is constructed based on twice Kalman filtering operation for acceleration correction. And the improved method can also increase the accuracy of target tracking through eliminating the interference of the similar targets in complex background. At the same time, by the multiple-object optimization of tracker, learner and detector, multiple objects can be tracked in single tracking process of single video frame. Experimental results show that tracking effect of improved method is better than that of the original TLD algorithm under the circumstance of similar target disturbance. Furthermore, the detection speed has been improved between 1.31x and 3.19x for different video and scenes. The improved method also does much better in case of targets vibration or distortion. At last, the multiple-object TLD-DO algorithm not only handles multiple-object tracking and inherits the characteristics of fast operation and strong anti-interference ability in TLD-DO, but also has a better identify processing capability that solve the problem in multiple similar objects tracking.