DocumentCode :
3363462
Title :
A New Approach to Track Moving Target with Improved Mean Shift Algorithm and Kalman Filter
Author :
Mu, Chengpo ; Yuan, Zhijie ; Song, Jia ; Chen, Yuanqian
Author_Institution :
Beijing Inst. of Technol., Beijing, China
Volume :
1
fYear :
2012
fDate :
26-27 Aug. 2012
Firstpage :
359
Lastpage :
362
Abstract :
In the application and prospect of computer vision technique, video target recognition and tracking was an important research subject. In this article, we present a new approach to track moving target with mean shift algorithm and kalman filter. With this approach, we do not need to calculate the Bhattacharyya coefficient, so we can track the moving target at real time. But we found that the robust of the track is not very well, so we use kalman filter to improve the effect of the track window. With simulation and experience, we prove that the new approach can Track the moving target in real time and the robust of the track is very well.
Keywords :
Kalman filters; computer vision; estimation theory; feature extraction; object recognition; object tracking; statistical analysis; video surveillance; Kalman filter; computer vision technique; intelligent video surveillance; kernel density estimation; mean shift algorithm; moving target tracking; statistical histogram; track window effect improvement; video target recognition; video target tracking; Covariance matrix; Histograms; Image color analysis; Kalman filters; Robustness; Signal processing algorithms; Target tracking; Kalman filter; Matlab simulation; color histogram; correction; mean shift algorithm; prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2012 4th International Conference on
Conference_Location :
Nanchang, Jiangxi
Print_ISBN :
978-1-4673-1902-7
Type :
conf
DOI :
10.1109/IHMSC.2012.96
Filename :
6305700
Link To Document :
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