Improving the Accuracy of Action Classification Using View-Dependent Context Information

  • Rodrigo Cilla
  • Miguel A. Patricio
  • Antonio Berlanga
  • José M. Molina
Conference paper

DOI: 10.1007/978-3-642-21222-2_17

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6679)
Cite this paper as:
Cilla R., Patricio M.A., Berlanga A., Molina J.M. (2011) Improving the Accuracy of Action Classification Using View-Dependent Context Information. In: Corchado E., Kurzyński M., Woźniak M. (eds) Hybrid Artificial Intelligent Systems. HAIS 2011. Lecture Notes in Computer Science, vol 6679. Springer, Berlin, Heidelberg

Abstract

This paper presents a human action recognition system that decomposes the task in two subtasks. First, a view-independent classifier, shared between the multiple views to analyze, is applied to obtain an initial guess of the posterior distribution of the performed action. Then, this posterior distribution is combined with view based knowledge to improve the action classification. This allows to reuse the view-independent component when a new view has to be analyzed, needing to only specify the view dependent knowledge. An example of the application of the system into an smart home domain is discussed.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Rodrigo Cilla
    • 1
  • Miguel A. Patricio
    • 1
  • Antonio Berlanga
    • 1
  • José M. Molina
    • 1
  1. 1.Computer Science DepartmentUniversidad Carlos III de MadridColmenarejo, MadridSpain

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