A mobile camera tracking system using GbLN-PSO with an adaptive window

The availability of high quality and inexpensive video camera, as well as the increasing need for automated video analysis is leading towards a great deal of interest in numerous applications. However the video tracking systems is still having many open problems. Thus, some of research activities in...

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Main Authors:	Zalili, Musa, Rohani, Abu Bakar, Watada, J.
Format:	Conference or Workshop Item
Language:	English
Published:	IEEE 2011
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/25562/ http://umpir.ump.edu.my/id/eprint/25562/ http://umpir.ump.edu.my/id/eprint/25562/1/A%20mobile%20camera%20tracking%20system%20using%20GbLN.pdf

id	ump-25562
recordtype	eprints
spelling	ump-255622019-12-12T04:52:58Z http://umpir.ump.edu.my/id/eprint/25562/ A mobile camera tracking system using GbLN-PSO with an adaptive window Zalili, Musa Rohani, Abu Bakar Watada, J. QA76 Computer software The availability of high quality and inexpensive video camera, as well as the increasing need for automated video analysis is leading towards a great deal of interest in numerous applications. However the video tracking systems is still having many open problems. Thus, some of research activities in a video tracking system are still being explored. Generally, most of the researchers are used a static camera in order to track an object motion. However, the use of a static camera system for detecting and tracking the motion of an object is only capable for capturing a limited view. Therefore, to overcome the above mentioned problem in a large view space, researcher may use several cameras to capture images. Thus, the cost will increases with the number of cameras. To overcome the cost increment a mobile camera is employed with the ability to track the wide field of view in an environment. Conversely, mobile camera technologies for tracking applications have faced several problems; simultaneous motion (when an object and camera are concurrently movable), distinguishing objects in occlusion, and dynamic changes in the background during data capture. In this study we propose a new method of Global best Local Neighborhood Oriented Particle Swarm Optimization (GbLN-PSO) to address these problems. The advantages of tracking using GbLN-PSO are demonstrated in experiments for intelligent human and vehicle tracking systems in comparison to a conventional method. The comparative study of the method is provided to evaluate its capabilities at the end of this paper. IEEE 2011 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25562/1/A%20mobile%20camera%20tracking%20system%20using%20GbLN.pdf Zalili, Musa and Rohani, Abu Bakar and Watada, J. (2011) A mobile camera tracking system using GbLN-PSO with an adaptive window. In: 2nd International Conference on Computational Intelligence, Modelling and Simulation, 20-22 September 2011 , Langkawi, Kedah. pp. 259-264.. ISSN 2166-8531 ISBN 978-0-7695-4562-2 https://doi.org/10.1109/CIMSim.2011.53
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Zalili, Musa Rohani, Abu Bakar Watada, J. A mobile camera tracking system using GbLN-PSO with an adaptive window
description	The availability of high quality and inexpensive video camera, as well as the increasing need for automated video analysis is leading towards a great deal of interest in numerous applications. However the video tracking systems is still having many open problems. Thus, some of research activities in a video tracking system are still being explored. Generally, most of the researchers are used a static camera in order to track an object motion. However, the use of a static camera system for detecting and tracking the motion of an object is only capable for capturing a limited view. Therefore, to overcome the above mentioned problem in a large view space, researcher may use several cameras to capture images. Thus, the cost will increases with the number of cameras. To overcome the cost increment a mobile camera is employed with the ability to track the wide field of view in an environment. Conversely, mobile camera technologies for tracking applications have faced several problems; simultaneous motion (when an object and camera are concurrently movable), distinguishing objects in occlusion, and dynamic changes in the background during data capture. In this study we propose a new method of Global best Local Neighborhood Oriented Particle Swarm Optimization (GbLN-PSO) to address these problems. The advantages of tracking using GbLN-PSO are demonstrated in experiments for intelligent human and vehicle tracking systems in comparison to a conventional method. The comparative study of the method is provided to evaluate its capabilities at the end of this paper.
format	Conference or Workshop Item
author	Zalili, Musa Rohani, Abu Bakar Watada, J.
author_facet	Zalili, Musa Rohani, Abu Bakar Watada, J.
author_sort	Zalili, Musa
title	A mobile camera tracking system using GbLN-PSO with an adaptive window
title_short	A mobile camera tracking system using GbLN-PSO with an adaptive window
title_full	A mobile camera tracking system using GbLN-PSO with an adaptive window
title_fullStr	A mobile camera tracking system using GbLN-PSO with an adaptive window
title_full_unstemmed	A mobile camera tracking system using GbLN-PSO with an adaptive window
title_sort	mobile camera tracking system using gbln-pso with an adaptive window
publisher	IEEE
publishDate	2011
url	http://umpir.ump.edu.my/id/eprint/25562/ http://umpir.ump.edu.my/id/eprint/25562/ http://umpir.ump.edu.my/id/eprint/25562/1/A%20mobile%20camera%20tracking%20system%20using%20GbLN.pdf
first_indexed	2023-09-18T22:39:19Z
last_indexed	2023-09-18T22:39:19Z
_version_	1777416807913619456

A mobile camera tracking system using GbLN-PSO with an adaptive window

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