Using local saliency for object tracking with particle filters

Yanran Yuan, Chunxiao Gao, Qiongxin Liu, Jing Wang, Chengtao Zhang

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

5 Citations (Scopus)

Abstract

Particle filter shows great success in non-rigid object tracking. But tracking errors would be inevitable when the background changes greatly, or when the color distribution of background is similar to target's. To eliminate these errors, an improved method based on visual attention is proposed in this paper. In our algorithm, the extraction method based on visual attention is applied to extract salient region from target area and particle areas. Instead of saliency map of the whole image, we just compute saliency map of each particle to extract salient region. Experimental results show that the proposed method is more robust against background interference and illumination changes. Therefore, the target tracking is more stable.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages388-393
Number of pages6
ISBN (Electronic)9781479952748
DOIs
Publication statusPublished - 15 Dec 2014
Event2014 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2014 - Guilin, Guangxi, China
Duration: 5 Aug 20148 Aug 2014

Publication series

Name2014 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2014

Conference

Conference2014 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2014
Country/TerritoryChina
CityGuilin, Guangxi
Period5/08/148/08/14

Keywords

  • Particle filter
  • salient region
  • target tracking
  • visual attention

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