Robust vision-based multiple moving object detection and tracking from video sequences

Detection of Moving Objects and Tracking is one of the most concerned issue and is being vastly used at home, business and modern applications. It is used to identify and track of an entity in a significant way. This paper illustrates the way to detect multiple objects using background subtraction m...

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Main Authors:	Khalifa, Othman Omran, Abdul Malek, Norun, Ahmed, Kazi Istiaque, Abdul Rahman, Farah Diyana
Format:	Article
Language:	English English
Published:	IAES 2018
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/62561/ http://irep.iium.edu.my/62561/ http://irep.iium.edu.my/62561/ http://irep.iium.edu.my/62561/7/62561%20Robust%20vision-based%20multiple%20moving%20object%20detection%20SCOPUS.pdf http://irep.iium.edu.my/62561/13/62561_Robust%20vision-based%20multiple%20moving%20object%20detection_article.pdf

id	iium-62561
recordtype	eprints
spelling	iium-625612018-08-09T07:15:42Z http://irep.iium.edu.my/62561/ Robust vision-based multiple moving object detection and tracking from video sequences Khalifa, Othman Omran Abdul Malek, Norun Ahmed, Kazi Istiaque Abdul Rahman, Farah Diyana T Technology (General) Detection of Moving Objects and Tracking is one of the most concerned issue and is being vastly used at home, business and modern applications. It is used to identify and track of an entity in a significant way. This paper illustrates the way to detect multiple objects using background subtraction methods and extract each object features by using Speed-Up Robust Feature algorithm and track the features through k-Nearest Neighbor processing from different surveillance videos sequentially. In the detection of object of each frame, pixel difference is calculated with respect to the reference background frame for the detection of an object which is only suitable for any ideal static condition with the consideration of lights from the environment. Thus, this method will detect the complete object and the extracted feature will be carried out for the tracking of the object in the multiple videos by one by one video. It is expected that this proposed method can commendably abolish the impact of the changing of lights. IAES 2018-05 Article PeerReviewed application/pdf en http://irep.iium.edu.my/62561/7/62561%20Robust%20vision-based%20multiple%20moving%20object%20detection%20SCOPUS.pdf application/pdf en http://irep.iium.edu.my/62561/13/62561_Robust%20vision-based%20multiple%20moving%20object%20detection_article.pdf Khalifa, Othman Omran and Abdul Malek, Norun and Ahmed, Kazi Istiaque and Abdul Rahman, Farah Diyana (2018) Robust vision-based multiple moving object detection and tracking from video sequences. Indonesian Journal of Electrical Engineering and Computer Science, 10 (2). pp. 817-826. ISSN 2502-4752 http://www.iaescore.com/journals/index.php/IJEECS/article/view/11857/8412 10.11591/ijeecs.v10.i2.pp817-826
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	T Technology (General)
spellingShingle	T Technology (General) Khalifa, Othman Omran Abdul Malek, Norun Ahmed, Kazi Istiaque Abdul Rahman, Farah Diyana Robust vision-based multiple moving object detection and tracking from video sequences
description	Detection of Moving Objects and Tracking is one of the most concerned issue and is being vastly used at home, business and modern applications. It is used to identify and track of an entity in a significant way. This paper illustrates the way to detect multiple objects using background subtraction methods and extract each object features by using Speed-Up Robust Feature algorithm and track the features through k-Nearest Neighbor processing from different surveillance videos sequentially. In the detection of object of each frame, pixel difference is calculated with respect to the reference background frame for the detection of an object which is only suitable for any ideal static condition with the consideration of lights from the environment. Thus, this method will detect the complete object and the extracted feature will be carried out for the tracking of the object in the multiple videos by one by one video. It is expected that this proposed method can commendably abolish the impact of the changing of lights.
format	Article
author	Khalifa, Othman Omran Abdul Malek, Norun Ahmed, Kazi Istiaque Abdul Rahman, Farah Diyana
author_facet	Khalifa, Othman Omran Abdul Malek, Norun Ahmed, Kazi Istiaque Abdul Rahman, Farah Diyana
author_sort	Khalifa, Othman Omran
title	Robust vision-based multiple moving object detection and tracking from video sequences
title_short	Robust vision-based multiple moving object detection and tracking from video sequences
title_full	Robust vision-based multiple moving object detection and tracking from video sequences
title_fullStr	Robust vision-based multiple moving object detection and tracking from video sequences
title_full_unstemmed	Robust vision-based multiple moving object detection and tracking from video sequences
title_sort	robust vision-based multiple moving object detection and tracking from video sequences
publisher	IAES
publishDate	2018
url	http://irep.iium.edu.my/62561/ http://irep.iium.edu.my/62561/ http://irep.iium.edu.my/62561/ http://irep.iium.edu.my/62561/7/62561%20Robust%20vision-based%20multiple%20moving%20object%20detection%20SCOPUS.pdf http://irep.iium.edu.my/62561/13/62561_Robust%20vision-based%20multiple%20moving%20object%20detection_article.pdf
first_indexed	2023-09-18T21:28:39Z
last_indexed	2023-09-18T21:28:39Z
_version_	1777412362349838336

Robust vision-based multiple moving object detection and tracking from video sequences

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