A graph-kernel method for re-identification

  • Authors:
  • Luc Brun;Donatello Conte;Pasquale Foggia;Mario Vento

  • Affiliations:
  • GREYC UMR CNRS 6072, ENSICAEN-Université de Caen Basse-Normandie, Caen, France;Dipartimento di Ingegneria dell'Informazione e di Ingegneria Elettrica, Fisciano (SA), Italy;Dipartimento di Ingegneria dell'Informazione e di Ingegneria Elettrica, Fisciano (SA), Italy;Dipartimento di Ingegneria dell'Informazione e di Ingegneria Elettrica, Fisciano (SA), Italy

  • Venue:
  • ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
  • Year:
  • 2011

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Abstract

Re-identification, that is recognizing that an object appearing in a scene is a reoccurrence of an object seen previously by the system (by the same camera or possibly by a different one) is a challenging problem in video surveillance. In this paper, the problem is addressed using a structural, graph-based representation of the objects of interest. A recently proposed graph kernel is adopted for extending to this representation the Principal Component Analyisis (PCA) technique. An experimental evaluation of the method has been performed on two video sequences from the publicly available PETS2009 database.