Face detection hindering

Panteleimon Chriskos, Jonathan Munro, Vasileios Mygdalis, Ioannis Pitas

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

4 Citations (Scopus)
202 Downloads (Pure)

Abstract

In this paper, we develop a face detection hindering method, as a means of preventing the threats to people's privacy, automatic video analysis may pose. Face detection in images or videos is the first step in human-centered video analysis to be followed, e.g. by automatic face recognition. Therefore, by hindering face detection, we also render automatic face recognition improbable. To this end, we examine the application of two methods. First, we consider a naive approach, i.e., we simply use additive or impulsive noise to the input image, until the point where the face cannot be automatically detected anymore. Second, we examine the application of the SVD-DID face de-identification method. Our experimental results denote that both methods attain high face detection failure rates.

Original languageEnglish
Title of host publication2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP 2017)
Subtitle of host publicationProceedings of a meeting held 14-16 November 2017, Montreal, Quebec, Canada
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages403-407
Number of pages5
ISBN (Electronic)9781509059904
ISBN (Print)9781509059911
DOIs
Publication statusPublished - Apr 2018
Event5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Montreal, Canada
Duration: 14 Nov 201716 Nov 2017

Conference

Conference5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017
CountryCanada
CityMontreal
Period14/11/1716/11/17

Keywords

  • face de-identification
  • face detection
  • privacy protection
  • surveillance

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