Multi-scale Correlation Filter Tracking with Adaptive Re-detection Mechanism

Ruoling Yang, Tingfa Xu, Yu Bai, Axin Fan, Bo Yuan

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

Abstract

Tracking is a popular research topic in artificial intelligence, but how to handle the severe occlusion and deformation remains a challenging problem. Focusing on this issue, we propose a multi-scale correlation filter tracker using a re-detection module. Specifically, we utilize a reliable confidence strategy to estimate the reliability of initial results, and introduce a novel template matching technique to solve the target relocation problem. Experiment results demonstrate that our method can outperform several classic trackers.

Original languageEnglish
Title of host publicationProceedings of 2019 IEEE International Conference of Intelligent Applied Systems on Engineering, ICIASE 2019
EditorsTeen-Hang Meen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages305-308
Number of pages4
ISBN (Electronic)9781538681398
DOIs
Publication statusPublished - Apr 2019
Event2019 IEEE International Conference of Intelligent Applied Systems on Engineering, ICIASE 2019 - Fuzhou, Fujian, China
Duration: 26 Apr 201929 Apr 2019

Publication series

NameProceedings of 2019 IEEE International Conference of Intelligent Applied Systems on Engineering, ICIASE 2019

Conference

Conference2019 IEEE International Conference of Intelligent Applied Systems on Engineering, ICIASE 2019
Country/TerritoryChina
CityFuzhou, Fujian
Period26/04/1929/04/19

Keywords

  • adaptive re-detection
  • correlation filter
  • template matching

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