An efficient probabilistic occupancy map-based people localization approach

Yen Shuo Lin, Hua Tsung Chen, Jen-Hui Chuang

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

Abstract

The widespread use of vision-based video surveillance systems has inspired many research efforts on people localization. One of the current main trends in this field is based on probabilistic occupancy map (POM) obtained from multiple camera views. Although the POM-based approaches are robust against noisy foregrounds and can achieve great localization accuracy, they require high computation complexity. In this paper, two enhancement schemes are proposed to improve the efficiency of the POM-based people localization: (i) quick screening of potential people locations, and (ii) timely termination of iterations for occupancy probability estimation. Experimental results show that the proposed approach achieves up to 7.25 times speed-up compared to the standard POM-based approach, while delivering comparable people localization accuracy.

Original languageEnglish
Title of host publication2015 Visual Communications and Image Processing, VCIP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467373142
DOIs
StatePublished - 1 Jan 2015
EventVisual Communications and Image Processing, VCIP 2015 - Singapore, Singapore
Duration: 13 Dec 201516 Dec 2015

Publication series

Name2015 Visual Communications and Image Processing, VCIP 2015

Conference

ConferenceVisual Communications and Image Processing, VCIP 2015
CountrySingapore
CitySingapore
Period13/12/1516/12/15

Keywords

  • People localization
  • efficient algorithm
  • multiple cameras
  • probabilistic occupancy map
  • video surveillance

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