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Artificial Intelligence Review

, Volume 46, Issue 4, pp 515–541 | Cite as

Biometric recognition in surveillance scenarios: a survey

  • João Neves
  • Fabio Narducci
  • Silvio Barra
  • Hugo Proença
Article

Abstract

Interest in the security of individuals has increased in recent years. This increase has in turn led to much wider deployment of surveillance cameras worldwide, and consequently, automated surveillance systems research has received more attention from the scientific community than before. Concurrently, biometrics research has become more popular as well, and it is supported by the increasing number of approaches devised to address specific degradation factors of unconstrained environments. Despite these recent efforts, no automated surveillance system that performs reliable biometric recognition in such an environment has become available. Nevertheless, recent developments in human motion analysis and biometric recognition suggest that both can be combined to develop a fully automated system. As such, this paper reviews recent advances in both areas, with a special focus on surveillance scenarios. When compared to previous studies, we highlight two distinct features, i.e., (1) our emphasis is on approaches that are devised to work in unconstrained environments and surveillance scenarios; and (2) biometric recognition is the final goal of the surveillance system, as opposed to behavior analysis, anomaly detection or action recognition.

Keywords

Human motion analysis Surveillance Biometric recognition Scene understanding Detection Tracking  Recognition Unconstrained scenarios 

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • João Neves
    • 1
  • Fabio Narducci
    • 2
  • Silvio Barra
    • 2
  • Hugo Proença
    • 1
  1. 1.IT - Instituto de TelecomunicaçõesUniversity of Beira InteriorCovilhãPortugal
  2. 2.Institute of High Performance Computing and NetworkingNational Research Council of Italy (ICAR-CNR)NaplesItaly

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