A Robust Algorithm for Long-term Object Tracking Based on PTAV

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2019
EditorsBing Xu, Kefen Mou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2686-2693
Number of pages8
ISBN (Electronic)9781728119076
DOIs
Publication statusPublished - Dec 2019
Event4th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2019 - Chengdu, China
Duration: 20 Dec 201922 Dec 2019

Publication series

NameProceedings of 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2019

Conference

Conference4th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2019
Country/TerritoryChina
CityChengdu
Period20/12/1922/12/19

Keywords

  • PTAV
  • backtracking check
  • long-term object tracking
  • multi-peak detection

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