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29 October 2018 Silhouettes based human action recognition by Procrustes analysis and Fisher vector encoding
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Proceedings Volume 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence; 1083612 (2018) https://doi.org/10.1117/12.2506632
Event: 2018 International Conference on Image, Video Processing and Artificial Intelligence, 2018, Shanghai, China
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.
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Jiaxin Cai, Xin Tang, and Ranxu Zhong "Silhouettes based human action recognition by Procrustes analysis and Fisher vector encoding", Proc. SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, 1083612 (29 October 2018); https://doi.org/10.1117/12.2506632
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