Parallel tracker for visual object tracking

Xiangluan Liang, Ru Lai, Luzheng Bi

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

1 Citation (Scopus)

Abstract

In this paper, we present a novel tracker for real-time single object tracking by combining Kernelized Correlation Filter (KCF) and Distractor Aware Tracker (DAT). KCF is capable of distinguishing object from background efficiently while DAT is robust for object's appearance and similar distracting reigons. First, we propose a series­parallel connection structure to make full use of the two trackers's complementary advantages, which aims to locate the object position more accurately. Second, we add a revised scale filter to adapt the scale change. Experiments on OTB-100 demonstrate that our approach is better than both two sub-trackers and can run in real-time.

Original languageEnglish
Title of host publicationProceedings of the 30th Chinese Control and Decision Conference, CCDC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5676-5681
Number of pages6
ISBN (Electronic)9781538612439
DOIs
Publication statusPublished - 6 Jul 2018
Event30th Chinese Control and Decision Conference, CCDC 2018 - Shenyang, China
Duration: 9 Jun 201811 Jun 2018

Publication series

NameProceedings of the 30th Chinese Control and Decision Conference, CCDC 2018

Conference

Conference30th Chinese Control and Decision Conference, CCDC 2018
Country/TerritoryChina
CityShenyang
Period9/06/1811/06/18

Keywords

  • Correlation Filter
  • Distroctor Aware
  • Object Tracking
  • Scale Filter

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