Cover Image

Human action recognition using time delay input radial basis function networks

This paper presents a fast, vision-based method for the problem of human action representation and recognition. The first problem is addressed by constructing an action descriptor from spatiotemporal data of action silhouettes based on appearance and motion features. For action classification, a new...

Full description

Saved in:
Bibliographic Details
Main Authors: Kalhor, Davood, Aris, Ishak, Moaini, Trifa, Abdul Halin, Izhal
Format: Article
Language:English
Published: United Kingdom Simulation Society 2014
Online Access:http://psasir.upm.edu.my/id/eprint/37653/1/Human%20action%20recognition%20using%20time%20delay%20input%20radial%20basis%20function%20networks.pdf
http://psasir.upm.edu.my/id/eprint/37653/
http://ijssst.info/Vol-15/No-3/cover-15-3.htm
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.upm.eprints.37653
record_format eprints
spelling my.upm.eprints.376532017-10-30T06:11:03Z http://psasir.upm.edu.my/id/eprint/37653/ Human action recognition using time delay input radial basis function networks Kalhor, Davood Aris, Ishak Moaini, Trifa Abdul Halin, Izhal This paper presents a fast, vision-based method for the problem of human action representation and recognition. The first problem is addressed by constructing an action descriptor from spatiotemporal data of action silhouettes based on appearance and motion features. For action classification, a new Radial Basis Function Network (RBF), called Time Delay Input Radial Basis Function Network (TDIRBF) is proposed by introducing time delay units to the RBF in a novel approach. A TDIRBF offers a few desirable features such as an easier learning process and more flexibility. The representational power and speed of the proposed method were explored 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 was just about 20 ms/frame (or 50 fps) and the classifier speed was above 15 fps. Furthermore, the proposed approach demonstrated good performance in terms of both execution time and overall performance (a new performance measure that combines accuracy and speed into one metric). United Kingdom Simulation Society 2014 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/37653/1/Human%20action%20recognition%20using%20time%20delay%20input%20radial%20basis%20function%20networks.pdf Kalhor, Davood and Aris, Ishak and Moaini, Trifa and Abdul Halin, Izhal (2014) Human action recognition using time delay input radial basis function networks. International Journal of Simulation: Systems, Science & Technology, 15 (3). pp. 42-53. ISSN 1473-8031; ESSN: 1473-804X http://ijssst.info/Vol-15/No-3/cover-15-3.htm 10.5013/IJSSST.a.15.03.07
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description This paper presents a fast, vision-based method for the problem of human action representation and recognition. The first problem is addressed by constructing an action descriptor from spatiotemporal data of action silhouettes based on appearance and motion features. For action classification, a new Radial Basis Function Network (RBF), called Time Delay Input Radial Basis Function Network (TDIRBF) is proposed by introducing time delay units to the RBF in a novel approach. A TDIRBF offers a few desirable features such as an easier learning process and more flexibility. The representational power and speed of the proposed method were explored 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 was just about 20 ms/frame (or 50 fps) and the classifier speed was above 15 fps. Furthermore, the proposed approach demonstrated good performance in terms of both execution time and overall performance (a new performance measure that combines accuracy and speed into one metric).
format Article
author Kalhor, Davood
Aris, Ishak
Moaini, Trifa
Abdul Halin, Izhal
spellingShingle Kalhor, Davood
Aris, Ishak
Moaini, Trifa
Abdul Halin, Izhal
Human action recognition using time delay input radial basis function networks
author_facet Kalhor, Davood
Aris, Ishak
Moaini, Trifa
Abdul Halin, Izhal
author_sort Kalhor, Davood
title Human action recognition using time delay input radial basis function networks
title_short Human action recognition using time delay input radial basis function networks
title_full Human action recognition using time delay input radial basis function networks
title_fullStr Human action recognition using time delay input radial basis function networks
title_full_unstemmed Human action recognition using time delay input radial basis function networks
title_sort human action recognition using time delay input radial basis function networks
publisher United Kingdom Simulation Society
publishDate 2014
url http://psasir.upm.edu.my/id/eprint/37653/1/Human%20action%20recognition%20using%20time%20delay%20input%20radial%20basis%20function%20networks.pdf
http://psasir.upm.edu.my/id/eprint/37653/
http://ijssst.info/Vol-15/No-3/cover-15-3.htm
_version_ 1643832035647684608
score 13.211869

Similar Items