Behaviour-Based Object Classifier for Surveillance Videos

  • Virginia Fernandez Arguedas
  • Krishna Chandramouli
  • Ebroul Izquierdo
Conference paper

DOI: 10.1007/978-3-642-28033-7_10

Part of the Communications in Computer and Information Science book series (CCIS, volume 255)
Cite this paper as:
Fernandez Arguedas V., Chandramouli K., Izquierdo E. (2012) Behaviour-Based Object Classifier for Surveillance Videos. In: Moschitti A., Scandariato R. (eds) Eternal Systems. EternalS 2011. Communications in Computer and Information Science, vol 255. Springer, Berlin, Heidelberg

Abstract

In this paper, a study on effective exploitation of geometrical features for classifying surveillance objects into a set of pre-defined semantic categories is presented. The geometrical features correspond to object’s motion, spatial location and velocity. The extraction of these features is based on object’s trajectory corresponding to object’s temporal evolution. These geometrical features are used to build a behaviour-based classifier to assign semantic categories to the individual blobs extracted from surveillance videos. The proposed classification framework has been evaluated against conventional object classifiers based on visual features extracted from semantic categories defined on AVSS 2007 surveillance dataset.

Keywords

Object classification geometrical models surveillance videos object tracking motion features 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Virginia Fernandez Arguedas
    • 1
  • Krishna Chandramouli
    • 1
  • Ebroul Izquierdo
    • 1
  1. 1.Multimedia and Vision Research Group, School of Electronic Engineering and Computer ScienceQueen Mary, University of LondonLondonUK

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