Human action recognition based on radon transform

Yan Chen, Qiang Wu, Xiangjian He

Research output: Chapter in Book/Conference proceedingBook Chapterpeer-review

8 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationMultimedia Analysis, Processing and Communications
EditorsWeisi Lin, Dacheng Tao, Janusz Kacprzyk, Zhu Li, Ebroul Izquierdo, Haohong Wang
Number of pages21
Publication statusPublished - 2011
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
ISSN (Print)1860-949X

ASJC Scopus subject areas

  • Artificial Intelligence


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