A Robust Algorithm for Long term Object Tracking Based on PTAV
Long term object tracking is one of the most challenging problems in computer vision due to various factors such as deformation, abrupt motion, heavy occlusion and out of view. In this paper, we propose a tracking method based on Parallel Tracking and Verifying (PTAV) Firstly, we replace the fDSST tracker with a better performance tracker ECO HC. Then we add self test mechanism for the tracker, which include backtracking check using forward backward overlap rate and multi peak detection mechanism. At last, we modify the parallel framework between the tracker and the verifier in the PTAV, so that the algorithm can get timey feedback about the abnormal information. We perform experiments on the benchmark OTB 2015. Results show that our method has better accuracy and robustness in case of occlusion, out of view and other interference factors.
2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)