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Silhouette-based multi-view human action recognition in video

Aryanfar, Ali Hossein and Yaakob, Razali and Abdul Halin, Alfian and Sulaiman, Md. Nasir and Kasmiran, Khairul Azhar (2014) Silhouette-based multi-view human action recognition in video. In: International Conference on Computational Science and Technology (ICCST 2014), 27-28 Aug. 2014, Kota Kinabalu, Sabah.

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Abstract

In this paper, a human action recognition method is presented where pose features are represented using contour points of the human silhouette, and actions are learned by using sequences of multi-view contour points. The differences and divergences among actors performing the same action are handled by considering variations in shape and speed. Experimental results on the IXMAS dataset show promising success rates, exceeding that of existing multi-view human action recognition state-of-the-art techniques.

Item Type:Conference or Workshop Item (Paper)
Keyword:2D wavelet; C5.0 classifier; Contour points; Human action recognition; IXMAS dataset; Silhouette; Style
Faculty or Institute:Faculty of Computer Science and Information Technology
Publisher:IEEE
DOI Number:10.1109/ICCST.2014.7045004
Altmetrics:http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/ICCST.2014.7045004
ID Code:47813
Deposited By: Nabilah Mustapa
Deposited On:15 Jul 2016 17:16
Last Modified:15 Jul 2016 17:16

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