Cover Image

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...

Full description

Saved in:
Bibliographic Details
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/25562/1/A%20mobile%20camera%20tracking%20system%20using%20GbLN.pdf
http://umpir.ump.edu.my/id/eprint/25562/
https://doi.org/10.1109/CIMSim.2011.53
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.ump.umpir.25562
record_format eprints
spelling my.ump.umpir.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
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
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/25562/1/A%20mobile%20camera%20tracking%20system%20using%20GbLN.pdf
http://umpir.ump.edu.my/id/eprint/25562/
https://doi.org/10.1109/CIMSim.2011.53
_version_ 1654960218445971456
score 13.211869

Similar Items