Object tracking algorithm of adaptive kernel-bandwidth for mean-shift based on optical-flows

Qinlong He, Junzheng Wang, Jing Li

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

Abstract

To obtain and update the kernel-bandwidth, we present an adaptive bandwidth obtainment algorithm based on object contour extraction from optical-flow field. The combination of modified mountain cluster approach and fast scanning window contour extractor guarantees the speed of this algorithm. A novel ellipse detection method based on a modified RANSAC is adopted to reduce the noise. Experimental results demonstrate that the algorithm select the proper size of tracking kernel-bandwidth with minor extra computational overhead and keep up with the object robustly when the scale changed rapidly.

Original languageEnglish
Title of host publicationProceedings of the 32nd Chinese Control Conference, CCC 2013
PublisherIEEE Computer Society
Pages3586-3589
Number of pages4
ISBN (Print)9789881563835
Publication statusPublished - 18 Oct 2013
Event32nd Chinese Control Conference, CCC 2013 - Xi'an, China
Duration: 26 Jul 201328 Jul 2013

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference32nd Chinese Control Conference, CCC 2013
Country/TerritoryChina
CityXi'an
Period26/07/1328/07/13

Keywords

  • RANSAC
  • kernel bandwidth
  • mean shift
  • mountain cluster
  • object tracking

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