Human action recognition based on radon transform

Publication Type:
Chapter
Citation:
2011, 346 pp. 369 - 389
Issue Date:
2011-05-09
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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. © 2011 Springer-Verlag Berlin Heidelberg.
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