• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/

Tracking moving objects using particle filter and edge observation model


Hyoyeon Kim, Kisang Kim, Hyung-Il Choi, Journal of Internet Computing and Services, Vol. 17, No. 3, pp. 25-32, Jun. 2016
10.7472/jksii.2016.17.3.25, Full Text:
Keywords: Particle Filter, edge, observation model, object tracking

Abstract

In this paper, we propose a method that is tracking an object in real time using particle filter and the observation model with edge. First of all, the proposed method defines the object to be tracked in the initial frame. Then, it generates the edge observation model for the object to be tracked and a set of particles. It calculates the weight by comparing the average of the middle distance in eight-way of particle filter edge model with that in edge observation model, and then updates the weight with the calculated value. After resampling particles using the updated weights, it estimates the current location of the tracked object. Finally, this paper demonstrates the performance of the stable tracking through comparison with the existing method by using a number of experimental data.


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Cite this article
[APA Style]
Kim, H., Kim, K., & Choi, H. (2016). Tracking moving objects using particle filter and edge observation model. Journal of Internet Computing and Services, 17(3), 25-32. DOI: 10.7472/jksii.2016.17.3.25.

[IEEE Style]
H. Kim, K. Kim, H. Choi, "Tracking moving objects using particle filter and edge observation model," Journal of Internet Computing and Services, vol. 17, no. 3, pp. 25-32, 2016. DOI: 10.7472/jksii.2016.17.3.25.

[ACM Style]
Hyoyeon Kim, Kisang Kim, and Hyung-Il Choi. 2016. Tracking moving objects using particle filter and edge observation model. Journal of Internet Computing and Services, 17, 3, (2016), 25-32. DOI: 10.7472/jksii.2016.17.3.25.