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Proceedings Paper

Human action recognition using integrated model
Author(s): Yang Yi; Yikun Lin
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Paper Abstract

A novel action recognition framework based on integrated model is proposed in the paper. First, the covariance descriptor is utilized to extract features from video sequences, and then each class specific codebook is constructed and appended to the global codebook. A static model applying the template matching technique and a dynamic model employing the trigram model are learned to capture complementary information in an action. And lastly, an integrated model is used to estimate the confidence of the static and dynamic models and produces a reliable result. Comparative experiments show that our presented method achieves superior results over other state-of-the-art approaches. Keywords: human action recognition, covariance descriptor, integrated model

Paper Details

Date Published: 19 July 2013
PDF: 5 pages
Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88782H (19 July 2013); doi: 10.1117/12.2030544
Show Author Affiliations
Yang Yi, Sun Yat-sen Univ. (China)
Yikun Lin, Sun Yat-sen Univ. (China)


Published in SPIE Proceedings Vol. 8878:
Fifth International Conference on Digital Image Processing (ICDIP 2013)
Yulin Wang; Xie Yi, Editor(s)

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