Bayesian Multimodal Fusion in Forensic Applications

  • Virginia Fernandez Arguedas
  • Qianni Zhang
  • Ebroul Izquierdo
Conference paper

DOI: 10.1007/978-3-642-33885-4_47

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7585)
Cite this paper as:
Fernandez Arguedas V., Zhang Q., Izquierdo E. (2012) Bayesian Multimodal Fusion in Forensic Applications. In: Fusiello A., Murino V., Cucchiara R. (eds) Computer Vision – ECCV 2012. Workshops and Demonstrations. ECCV 2012. Lecture Notes in Computer Science, vol 7585. Springer, Berlin, Heidelberg

Abstract

The public location of CCTV cameras and their connexion with public safety demand high robustness and reliability from surveillance systems. This paper focuses on the development of a multimodal fusion technique which exploits the benefits of a Bayesian inference scheme to enhance surveillance systems’ reliability. Additionally, an automatic object classifier is proposed based on the multimodal fusion technique, addressing semantic indexing and classification for forensic applications. The proposed Bayesian-based Multimodal Fusion technique, and particularly, the proposed object classifier are evaluated against two state-of-the-art automatic object classifiers on the i-LIDS surveillance dataset.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Virginia Fernandez Arguedas
    • 1
  • Qianni Zhang
    • 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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