Flow Guided Short-Term Trackers with Cascade Detection for Long-Term Tracking

Han Wu, Xueyuan Yang, Yong Yang, Guizhong Liu; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 0-0

Abstract

Object tracking has been studied for decades, but most of the existing works are focused on the short-term tracking. For a long sequence, the object is often fully occluded or out of view for a long time, and existing short-term object tracking algorithms often lose the target, and it is difficult to re-catch the target even if it reappears again. In this paper a novel long-term object tracking algorithm flow_MDNet_RPN is proposed, in which a tracking result judgement module and a detection module are added to the short-term object tracking algorithm. Experiments show that the proposed long-term tracking algorithm is effective to the problem of target disappearance.

Related Material

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[bibtex]
@InProceedings{Wu_2019_ICCV,
author = {Wu, Han and Yang, Xueyuan and Yang, Yong and Liu, Guizhong},
title = {Flow Guided Short-Term Trackers with Cascade Detection for Long-Term Tracking},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2019}
}