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

김영주 (신라대학교 컴퓨터공학과 멀티미디어통신연구실)
김광백 (퍼지신경망 및 의료영상처리연구실)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.28, no.10C, 2003 , pp. 1013-1022 More about this Journal
Abstract
This paper implemented the real-time 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 l/2.5∼1/50 of one of the traditional tracking method based on linear Kalman filter.
Keywords
Object Tracking; Non-parametric Thresholding; Dynamic AR(2) Process; Kalman Filter;
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