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Real Time Detection of Social Interactions in Surveillance Video

  • Paolo Rota
  • Nicola Conci
  • Nicu Sebe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7585)

Abstract

In this paper we present a novel method to detect the presence of social interactions occurring in a surveillance scenario. The algorithm we propose complements motion features with proxemics cues, so as to link the human motion with the contextual and environmental information. The extracted features are analyzed through a multi-class SVM. Testing has been carried out distinguishing between casual and intentional interactions, where intentional events are further subdivided into normal and abnormal behaviors. The algorithm is validated on benchmark datasets, as well as on a new dataset specifically designed for interactions analysis.

Keywords

Video Sequence Surveillance Video Real Time Detection Casual Interaction Social Force Model 
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-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Paolo Rota
    • 1
  • Nicola Conci
    • 1
  • Nicu Sebe
    • 1
  1. 1.University of TrentoPovoItaly

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