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

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

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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.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Dynamic tracking; Particle swarm optimization; Adaptive window; Pattern matching; Mobile camera
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 12 Dec 2019 04:52
Last Modified: 12 Dec 2019 04:52
URI: http://umpir.ump.edu.my/id/eprint/25562
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