Real-time human activity recognition using external and internal spatial features

Human activity recognition has become very popular in the field of computer vision. In this paper, we present a simple, robust and computationally efficient algorithm, architecture and implementation to recognise and classify human activities in real-time using very few training data. We employ a sp...

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Main Authors: Htike@Muhammad Yusof, Zaw Zaw, Egerton, Simon, Kuang, Ye Chow
Format: Conference or Workshop Item
Language:English
Published: 2010
Subjects:
Online Access:http://irep.iium.edu.my/43202/
http://irep.iium.edu.my/43202/
http://irep.iium.edu.my/43202/1/IE_2010_-_1.PDF
id iium-43202
recordtype eprints
spelling iium-432022015-06-08T03:34:55Z http://irep.iium.edu.my/43202/ Real-time human activity recognition using external and internal spatial features Htike@Muhammad Yusof, Zaw Zaw Egerton, Simon Kuang, Ye Chow AI Indexes (General) Human activity recognition has become very popular in the field of computer vision. In this paper, we present a simple, robust and computationally efficient algorithm, architecture and implementation to recognise and classify human activities in real-time using very few training data. We employ a spatio-temporal representation of human activities by combining trajectory information and invariant spatial information of the subjects. Activities are classified by a support vector machine (SVM) with a radial basis kernel. Optimal parameters for the SVM are found through a 10-fold cross-validation. Experimental results demonstrate that the proposed system is effective and efficient. When tested on the Weizmann dataset, the system achieves a recognition rate above 90% for one-shot learning which is above benchmark scores in accordance with the literature. The system is also found to be robust against noise, deformation and variation in viewpoints. The system is feasible to operate efficiently in real-time and deployable in intelligent environments. 2010-07-19 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/43202/1/IE_2010_-_1.PDF Htike@Muhammad Yusof, Zaw Zaw and Egerton, Simon and Kuang, Ye Chow (2010) Real-time human activity recognition using external and internal spatial features. In: Sixth International Conference on Intelligent Environments (IE), 19-21 July 2010, Kuala Lumpur, Malaysia. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5673973
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic AI Indexes (General)
spellingShingle AI Indexes (General)
Htike@Muhammad Yusof, Zaw Zaw
Egerton, Simon
Kuang, Ye Chow
Real-time human activity recognition using external and internal spatial features
description Human activity recognition has become very popular in the field of computer vision. In this paper, we present a simple, robust and computationally efficient algorithm, architecture and implementation to recognise and classify human activities in real-time using very few training data. We employ a spatio-temporal representation of human activities by combining trajectory information and invariant spatial information of the subjects. Activities are classified by a support vector machine (SVM) with a radial basis kernel. Optimal parameters for the SVM are found through a 10-fold cross-validation. Experimental results demonstrate that the proposed system is effective and efficient. When tested on the Weizmann dataset, the system achieves a recognition rate above 90% for one-shot learning which is above benchmark scores in accordance with the literature. The system is also found to be robust against noise, deformation and variation in viewpoints. The system is feasible to operate efficiently in real-time and deployable in intelligent environments.
format Conference or Workshop Item
author Htike@Muhammad Yusof, Zaw Zaw
Egerton, Simon
Kuang, Ye Chow
author_facet Htike@Muhammad Yusof, Zaw Zaw
Egerton, Simon
Kuang, Ye Chow
author_sort Htike@Muhammad Yusof, Zaw Zaw
title Real-time human activity recognition using external and internal spatial features
title_short Real-time human activity recognition using external and internal spatial features
title_full Real-time human activity recognition using external and internal spatial features
title_fullStr Real-time human activity recognition using external and internal spatial features
title_full_unstemmed Real-time human activity recognition using external and internal spatial features
title_sort real-time human activity recognition using external and internal spatial features
publishDate 2010
url http://irep.iium.edu.my/43202/
http://irep.iium.edu.my/43202/
http://irep.iium.edu.my/43202/1/IE_2010_-_1.PDF
first_indexed 2023-09-18T21:01:34Z
last_indexed 2023-09-18T21:01:34Z
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