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A Multiple Kernel Learning Based Fusion Framework for Real-Time Multi-View Action Recognition

  • Feng Gu
  • Francisco Flórez-Revuelta
  • Dorothy Monekosso
  • Paolo Remagnino
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8868)

Abstract

Due to the increasing demand of multi-camera setup and long-term monitoring in vision applications, real-time multi-view action recognition has gain a great interest in recent years. In this paper, we propose a multiple kernel learning based fusion framework that employs a motion-based person detector for finding regions of interest and local descriptors with bag-of-words quantisation for feature representation. The experimental results on a multi-view action dataset suggest that the proposed framework significantly outperforms simple fusion techniques and state-of-the-art methods.

Keywords

Action Recognition Camera View Multiple Kernel Multiple Kernel Learning Human Action Recognition 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • Feng Gu
    • 1
  • Francisco Flórez-Revuelta
    • 1
  • Dorothy Monekosso
    • 1
  • Paolo Remagnino
    • 1
  1. 1.Digital Imaging Research CentreKingston UniversityLondonUK

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