Enhancement of Particle Filter Resampling in Vehicle Tracking via Genetic Algorithm
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Date
2012
Journal Title
Journal ISSN
Volume Title
Publisher
UKSim-AMSS 6th European Modelling Symposium
Abstract
Vehicle tracking is an essential approach that can help to improve the traffic surveillance or assist the road traffic control. Recently, the development of video surveillance infrastructure has incited the researchers to focus on the vehicle tracking by using video sensors. However, the amount of the on-road vehicle has been increased dramatically and hence the congestion of the traffic has made the occlusion scene become a challenge task for video sensor based tracking. Conventional particle filter will encounter tracking error during and after occlusion. Besides that, it also required more iteration to continuously track the vehicle after occlusion. Thus, particle filter with genetic operator resampling has been proposed as the tracking algorithm to faster converge and keep track on the target vehicle under various occlusion incidents. The experimental results show that enhancement of the particle filter with genetic algorithm manage to reduce the particle sample size.
Description
Modelling, Simulation & Computing Laboratory, Material & Mineral Research Unit
School of Engineering and Information Technology
Universiti Malaysia Sabah
Kota Kinabalu, Malaysia
msclab@ums.edu.my, ktkteo@ieee.org
Keywords
TECHNOLOGY::Engineering mechanics::Vehicle engineering