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Human Action Recognition Based on Radon Transform

  • Yan Chen
  • Qiang Wu
  • Xiangjian He
Part of the Studies in Computational Intelligence book series (SCI, volume 346)

Abstract

A new feature description is used for human action representation and recognition. Features are extracted from the Radon transforms of silhouette images. Using the features, key postures are selected. Key postures are combined to construct an action template for each action sequence. Linear Discriminant Analysis (LDA) is applied to obtain low dimensional feature vectors. Different classification methods are used for human action recognition. Experiments are carried out based on a publicly available human action database.

Keywords

Linear Discriminant Analysis Independent Component Analysis Action Sequence Independent Component Analysis Action Video 
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 2011

Authors and Affiliations

  • Yan Chen
    • 1
  • Qiang Wu
    • 1
  • Xiangjian He
    • 1
  1. 1.Centre for Innovation in IT Services and Applications (iNext)University of TechnologySydneyAustralia

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