Silhouette-based multi-view human action recognition in video

Citation

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. .

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.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Computer Science and Information Technology
DOI Number:	https://doi.org/10.1109/ICCST.2014.7045004
Publisher:	IEEE
Keywords:	2D wavelet; C5.0 classifier; Contour points; Human action recognition; IXMAS dataset; Silhouette; Style
Depositing User:	Nabilah Mustapa
Date Deposited:	15 Jul 2016 09:16
Last Modified:	15 Jul 2016 09:16
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/ICCST.2014.7045004
URI:	http://psasir.upm.edu.my/id/eprint/47813
Statistic Details:	View Download Statistic

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