JACIII Vol.15 No.6 pp. 681-686
doi: 10.20965/jaciii.2011.p0681


Particle Filter with Gaussian Weighting for Vehicle Tracking

Indah Agustien Siradjuddin*
and Muhammad Rahmat Widyanto**

*Faculty of Engineering, Trunojoyo University, Telang Raya Street, Kamal Bangkalan, Madura Island, East Java, Indonesia

**Faculty of Computer Science, University of Indonesia, Depok Campus, West Java, Indonesia

December 14, 2010
April 27, 2011
August 20, 2011
particle filter, Bayesian, prediction, filtering, tracking
To track vehicle motion in data video, particle filter with Gaussian weighting is proposed. This method consists of four main stages. First, particles are generated to predict target’s location. Second, certain particles are searched and these particles are used to build Gaussian distribution. Third, weight of all particles is calculated based on Gaussian distribution. Fourth, particles are updated based on each weight. The proposed method could reduce computational time of tracking compared to that of conventional method of particle filter, since the proposed method does not have to calculate all particles weight using likelihood function. This method has been tested on video data with car as a target object. In average, this proposed method of particle filter is 60.61% times faster than particle filter method meanwhile the accuracy of tracking with this newmethod is comparable with particle filter method, which reach up to 86.87%. Hence this method is promising for real time object tracking application.
Cite this article as:
I. Siradjuddin and M. Widyanto, “Particle Filter with Gaussian Weighting for Vehicle Tracking,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.6, pp. 681-686, 2011.
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Last updated on Jun. 03, 2024