Multiple moving objects tracking for automated visual surveillance

Yuxiang Sun, Max Q.H. Meng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

Moving objects tracking is of great significance for automated visual surveillance. Conventional tracking algorithms, such as Kalman filter or particle filter, have shown the effectiveness and robustness in many practical applications. However, the Bayesian filter is not designed for tacking multiple moving objects. The difficulty is the data association between the measurements and the tracks. Tracking can fail due to the confusion of similar measurements from adjacent moving objects. This paper proposes an approach for multiple moving objects tracking. We formulate the measurement assignment process as a problem of finding the matching with the maximum weight in a bipartite graph. Moving objects are detected by background subtraction. We test our approach using public datasets. The experimental results demonstrate that our approach is able to track multiple moving objects correctly.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics
PublisherIEEE
Pages1617-1621
Number of pages5
ISBN (Electronic)9781467391047
DOIs
Publication statusPublished - 28 Sep 2015
Event2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics - Yunnan, China
Duration: 8 Aug 201510 Aug 2015

Publication series

Name2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics

Conference

Conference2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics
Country/TerritoryChina
CityYunnan
Period8/08/1510/08/15

Keywords

  • Noise

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Human-Computer Interaction
  • Computational Theory and Mathematics
  • Control and Systems Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Cite this