Multi-camera surveillance with visual tagging and generic camera placement

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

35 Scopus citations

Abstract

A common goal in many vision applications is to identify and track human objects with distinctive visual features or "tags". Examples range from identifying distinct soccer player by his jersey number to locating the face of an individual that produces a match in a face recognition system. In this paper, we made two contributions to this "visual tagging" problem. First, we propose a general framework for camera placement. This framework can measure the performance of any particular camera placement using simulation method. The optimal placement strategy can be obtained by iterative grid-based linear programming. Second, we focus on tracking specific colored tags used in a privacy-protecting visual surveillance network. By building a color classifier for tag detection and using epipolar geometry between multiple cameras for occlusion handling, our proposed system can identify, track and visually obfuscate individuals whose privacy in the surveillance video needs to be protected.

Original languageEnglish
Title of host publication2007 1st ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC
Pages259-266
Number of pages8
DOIs
StatePublished - 2007
Event2007 First ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC-07 - Vienna, Austria
Duration: Sep 25 2007Sep 28 2007

Publication series

Name2007 1st ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC

Conference

Conference2007 First ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC-07
Country/TerritoryAustria
CityVienna
Period9/25/079/28/07

Keywords

  • Camera placement
  • Epipolar geometry
  • Multi-camera tracking
  • Privacy protection
  • Visual tags

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition

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