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A fast approach for human action recognition


Citation

Kalhor, Davood and Aris, Ishak and Abdul Halin, Izhal and Moaini, Trifa (2014) A fast approach for human action recognition. In: Fifth International Conference on Intelligent Systems, Modelling and Simulation (ISMS 2014), 27-29 Jan. 2014, Langkawi, Kedah, Malaysia. (pp. 266-272).

Abstract

This paper presents a fast approach to represent and recognize human actions. For representation, a feature vector is constructed from spatiotemporal data of silhouettes based on appearance and motion. For classification, a new Radial Basis Function Network (RBF), called Time Delay Input Radial Basis Function Network is proposed by introducing time delay units to the RBF in a novel approach. The proposed network has a few desirable features such as easier learning process and more flexibility. The representational power and speed of the proposed method for action recognition were evaluated using a publicly available dataset. Based on experimental results, implemented in MATLAB and on standard PCs, the average time for constructing a feature vector for a high-resolution video is almost 20 ms/frame. Furthermore, the proposed approach demonstrates good performance in terms of execution time and overall performance (a new performance measure that combines accuracy and speed into one metric).


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Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.1109/ISMS.2014.52
Publisher: IEEE
Keywords: Action recognition; Action representation; Motion descriptor; Neural network; Radial basis function network
Depositing User: Nursyafinaz Mohd Noh
Date Deposited: 28 Oct 2015 04:12
Last Modified: 30 Oct 2017 06:19
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/ISMS.2014.52
URI: http://psasir.upm.edu.my/id/eprint/41158
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