Real-time human activity recognition

The traditional Closed-circuit Television (CCTV) system requires human to monitor the CCTV for 24/7 which is inefficient and costly. Therefore, there’s a need for a system which can recognize human activity effectively in real-time. This paper concentrates on recognizing simple activity such as w...

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Main Authors: Albukhary, N., Mohd. Mustafah, Yasir
Format: Proceeding Paper
Language:English
English
Published: IOP Publishing 2017
Subjects:
Online Access:http://irep.iium.edu.my/62903/
http://irep.iium.edu.my/62903/1/62903%20Real-time%20Human%20Activity%20Recognition.pdf
http://irep.iium.edu.my/62903/2/62903%20Real-time%20Human%20Activity%20Recognition%20SCOPUS.pdf
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author Albukhary, N.
Mohd. Mustafah, Yasir
author_facet Albukhary, N.
Mohd. Mustafah, Yasir
author_sort Albukhary, N.
building IIUM Repository
collection Online Access
description The traditional Closed-circuit Television (CCTV) system requires human to monitor the CCTV for 24/7 which is inefficient and costly. Therefore, there’s a need for a system which can recognize human activity effectively in real-time. This paper concentrates on recognizing simple activity such as walking, running, sitting, standing and landing by using image processing techniques. Firstly, object detection is done by using background subtraction to detect moving object. Then, object tracking and object classification are constructed so that different person can be differentiated by using feature detection. Geometrical attributes of tracked object, which are centroid and aspect ratio of identified tracked are manipulated so that simple activity can be detected.
first_indexed 2025-11-14T17:00:56Z
format Proceeding Paper
id iium-62903
institution International Islamic University Malaysia
institution_category Local University
language English
English
last_indexed 2025-11-14T17:00:56Z
publishDate 2017
publisher IOP Publishing
recordtype eprints
repository_type Digital Repository
spelling iium-629032018-06-26T08:09:40Z http://irep.iium.edu.my/62903/ Real-time human activity recognition Albukhary, N. Mohd. Mustafah, Yasir T Technology (General) The traditional Closed-circuit Television (CCTV) system requires human to monitor the CCTV for 24/7 which is inefficient and costly. Therefore, there’s a need for a system which can recognize human activity effectively in real-time. This paper concentrates on recognizing simple activity such as walking, running, sitting, standing and landing by using image processing techniques. Firstly, object detection is done by using background subtraction to detect moving object. Then, object tracking and object classification are constructed so that different person can be differentiated by using feature detection. Geometrical attributes of tracked object, which are centroid and aspect ratio of identified tracked are manipulated so that simple activity can be detected. IOP Publishing 2017-11-07 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/62903/1/62903%20Real-time%20Human%20Activity%20Recognition.pdf application/pdf en http://irep.iium.edu.my/62903/2/62903%20Real-time%20Human%20Activity%20Recognition%20SCOPUS.pdf Albukhary, N. and Mohd. Mustafah, Yasir (2017) Real-time human activity recognition. In: 6th International Conference on Mechatronics - ICOM'17, 8th–9th August 2017, Kuala Lumpur, Malaysia. http://iopscience.iop.org/article/10.1088/1757-899X/260/1/012017/pdf 10.1088/1757-899X/260/1/012017
spellingShingle T Technology (General)
Albukhary, N.
Mohd. Mustafah, Yasir
Real-time human activity recognition
title Real-time human activity recognition
title_full Real-time human activity recognition
title_fullStr Real-time human activity recognition
title_full_unstemmed Real-time human activity recognition
title_short Real-time human activity recognition
title_sort real-time human activity recognition
topic T Technology (General)
url http://irep.iium.edu.my/62903/
http://irep.iium.edu.my/62903/
http://irep.iium.edu.my/62903/
http://irep.iium.edu.my/62903/1/62903%20Real-time%20Human%20Activity%20Recognition.pdf
http://irep.iium.edu.my/62903/2/62903%20Real-time%20Human%20Activity%20Recognition%20SCOPUS.pdf