Enhancement of particle filter resampling in vehicle tracking via genetic algorithm

Wei Leong Khong, Wei Yeang Kow, Yit Kwong Chin, Mei Yeen Choong, Kenneth Tze Kin Teo

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

8 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationProceedings - UKSim-AMSS 6th European Modelling Symposium, EMS 2012
Number of pages6
Publication statusPublished - 2012
Externally publishedYes
EventUKSim-AMSS European Modelling Symposium on Computer Modelling and Simulation (EMS) 2012 - Malta, Malta
Duration: 14 Nov 201216 Nov 2012
Conference number: 6th
https://ieeexplore.ieee.org/xpl/conhome/6409604/proceeding (Proceedings)


ConferenceUKSim-AMSS European Modelling Symposium on Computer Modelling and Simulation (EMS) 2012
Abbreviated titleEMS 2012
Internet address


  • Genetic Algorithm
  • Particle filter
  • Resampling
  • Vehicle tracking

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