Privacy preserving video surveillance using pedestrian tracking mechanism

Peng Zhang, Tony Thomas, Sabu Emmanuel, Mohan S. Kankanhalli

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

14 Scopus citations

Abstract

Video surveillance has become a ubiquitous feature of the modern day life. However, the widespread use of video surveillance has raised concerns about the privacy of people. In this paper, we propose a novel video surveillance with a privacy preserving mechanism. We achieve this by combining the techniques of pedestrian tracking based on a Markov chain with two hidden states, elliptical head contour detection and encryption. The detected pedestrian face/head is obscured by encrypting with a unique key derived from a master key for the privacy preservation purpose. The surveillance video can be viewed with complete privacy or by revoking the privacy of any subset of pedestrians while ensuring complete privacy of the remaining pedestrians. The performance evaluation on many challenging surveillance scenarios shows that the proposed mechanism can effectively and robustly track multiple pedestrians and obscure their faces/head in real time.

Original languageEnglish
Title of host publicationMiFor'10 - Proceedings of the 2010 ACM Workshop on Multimedia in Forensics, Security and Intelligence, Co-located with ACM Multimedia 2010
Pages31-36
Number of pages6
DOIs
StatePublished - 2010
Externally publishedYes
EventMiFor'10 - Proceedings of the 2010 ACM Workshop on Multimedia in Forensics, Security and Intelligence, Co-located with ACM Multimedia 2010 - Firenze, Italy
Duration: 29 Oct 201029 Oct 2010

Publication series

NameMiFor'10 - Proceedings of the 2010 ACM Workshop on Multimedia in Forensics, Security and Intelligence, Co-located with ACM Multimedia 2010

Conference

ConferenceMiFor'10 - Proceedings of the 2010 ACM Workshop on Multimedia in Forensics, Security and Intelligence, Co-located with ACM Multimedia 2010
Country/TerritoryItaly
CityFirenze
Period29/10/1029/10/10

Keywords

  • Pedestrian tracking
  • Privacy
  • Video surveillance

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