PSO-based multiple people tracking

Ching Han Chen, Miao Chun Yan

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

4 Scopus citations

Abstract

In tracking applications, the task is a dynamic optimization problem which may be influenced by the object state and the time. In this paper, we present a robust human tracking by the particle swarm optimization (PSO) algorithm as a search strategy. We separate our system into two parts: human detection and human tracking. For human detection, considering the active camera, we do temporal differencing to detect the regions of interest. For human tracking, avoid losing tracking from unobvious movement of moving people, we implement the PSO algorithm. The particles fly around the search region to get an optimal match of the target. The appearance of the targets is modeled by feature vector and histogram. Experiments show the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationDigital Information and Communication Technology and Its Applications - International Conference, DICTAP 2011, Proceedings
Pages267-276
Number of pages10
EditionPART 1
DOIs
StatePublished - 2011
EventInternational Conference on Digital Information and Communication Technology and Its Applications, DICTAP 2011 - Dijon, France
Duration: 21 Jun 201123 Jun 2011

Publication series

NameCommunications in Computer and Information Science
NumberPART 1
Volume166 CCIS
ISSN (Print)1865-0929

Conference

ConferenceInternational Conference on Digital Information and Communication Technology and Its Applications, DICTAP 2011
Country/TerritoryFrance
CityDijon
Period21/06/1123/06/11

Keywords

  • Motion Detection
  • Object Tracking
  • Optimization
  • PSO

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