Quis-Campi: Extending in the Wild Biometric Recognition to Surveillance Environments

  • João C. Neves
  • Gil SantosEmail author
  • Sílvio Filipe
  • Emanuel Grancho
  • Silvio Barra
  • Fabio Narducci
  • Hugo Proença
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9281)


Efforts in biometrics are being held into extending robust recognition techniques to in the wild scenarios. Nonetheless, and despite being a very attractive goal, human identification in the surveillance context remains an open problem. In this paper, we introduce a novel biometric system – Quis-Campi – that effectively bridges the gap between surveillance and biometric recognition while having a minimum amount of operational restrictions. We propose a fully automated surveillance system for human recognition purposes, attained by combining human detection and tracking, further enhanced by a PTZ camera that delivers data with enough quality to perform biometric recognition. Along with the system concept, implementation details for both hardware and software modules are provided, as well as preliminary results over a real scenario.


Area Under Curve Equal Error Rate Biometric System Recognition Module Iris Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • João C. Neves
    • 1
  • Gil Santos
    • 1
    Email author
  • Sílvio Filipe
    • 1
  • Emanuel Grancho
    • 1
  • Silvio Barra
    • 2
  • Fabio Narducci
    • 3
  • Hugo Proença
    • 1
  1. 1.Department of Computer Science, IT - Instituto de TelecomunicaçõesUniversity of Beira InteriorCovilhãPortugal
  2. 2.DMI - Dipartimento di Matematica e InformaticaUniversity of CagliariCagliaryItaly
  3. 3.DISTRA-MITUniversity of SalernoFiscianoItaly

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