Bayesian Multimodal Fusion in Forensic Applications

  • Virginia Fernandez Arguedas
  • Qianni Zhang
  • Ebroul Izquierdo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7585)


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.


Support Vector Machine Bayesian Network Surveillance Video Fusion Technique Partial Decision 
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

  • 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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