Implementation of Real-time Object Tracking Algorithm based on Non-parametric Difference Picture and Kalman Filter 


Vol. 28,  No. 10, pp. 1013-1022, Oct.  2003


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  Abstract

This paper implemented the real-rime object tracking algorithm that extracts and tracks the moving object adaptively to input frame sequence by using non-parametric image processing method and Kalman filter-based dynamic AR(2) process method. By applying non-parametric image processing to input frames, the moving object was extracted from the background adaptively to diverse environmental conditions. And the movement of object was able to be adaptively estimated and tracked by modeling the various movement of object as dynamic AR(2) process and estimating based on the Kalman filter the parameters of AR(2) process dynamically changing along time. The experiments of the. implemented object tracking system showed that the proposed method tracked the moving object as more approximately as the estimation error became about 1/2.5-1/50 of one of the traditional.

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  Cite this article

[IEEE Style]

Y. Kim and K. Kim, "Implementation of Real-time Object Tracking Algorithm based on Non-parametric Difference Picture and Kalman Filter," The Journal of Korean Institute of Communications and Information Sciences, vol. 28, no. 10, pp. 1013-1022, 2003. DOI: .

[ACM Style]

Young-Ju Kim and Kwang-Baek Kim. 2003. Implementation of Real-time Object Tracking Algorithm based on Non-parametric Difference Picture and Kalman Filter. The Journal of Korean Institute of Communications and Information Sciences, 28, 10, (2003), 1013-1022. DOI: .

[KICS Style]

Young-Ju Kim and Kwang-Baek Kim, "Implementation of Real-time Object Tracking Algorithm based on Non-parametric Difference Picture and Kalman Filter," The Journal of Korean Institute of Communications and Information Sciences, vol. 28, no. 10, pp. 1013-1022, 10. 2003.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880