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Silhouettes based human action recognition by Procrustes analysis and Fisher vector encoding
Author(s): Jiaxin Cai; Xin Tang; Ranxu Zhong
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Paper Abstract

Recently, human action recognition in videos has attracted much attention. This paper proposed a framework for human action recognition based on procrustes analysis and Fisher vector encoding. First, we apply a pose based feature extracted from silhouette image by employing Procrustes analysis and local preserving projection. It can preserve the discriminative shape information and local manifold structure of human pose and is invariant to translation, rotation and scaling. After the pose feature is extracted, a recognition framework based on Fisher vector encoding and multi-class supporting vector machine is employed for classifying the human action. Experimental results on benchmarks demonstrate the effectiveness of the proposed method.

Paper Details

Date Published: 29 October 2018
PDF: 5 pages
Proc. SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, 1083612 (29 October 2018); doi: 10.1117/12.2506632
Show Author Affiliations
Jiaxin Cai, Xiamen Univ. of Technology (China)
Xin Tang, Huazhong Agricultural Univ. (China)
Ranxu Zhong, Guangdong Grandmark Automotive Systems Co., Ltd. (China)


Published in SPIE Proceedings Vol. 10836:
2018 International Conference on Image and Video Processing, and Artificial Intelligence
Ruidan Su, Editor(s)

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