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Proceedings Paper

Object tracking algorithm based on the color histogram probability distribution
Author(s): Ning Li; Tongwei Lu; Yanduo Zhang
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Paper Abstract

In order to resolve tracking failure resulted from target’s being occlusion and follower jamming caused by objects similar to target in the background, reduce the influence of light intensity. This paper change HSV and YCbCr color channel correction the update center of the target, continuously updated image threshold self-adaptive target detection effect, Clustering the initial obstacles is roughly range, shorten the threshold range, maximum to detect the target. In order to improve the accuracy of detector, this paper increased the Kalman filter to estimate the target state area. The direction predictor based on the Markov model is added to realize the target state estimation under the condition of background color interference and enhance the ability of the detector to identify similar objects. The experimental results show that the improved algorithm more accurate and faster speed of processing.

Paper Details

Date Published: 10 April 2018
PDF: 6 pages
Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106150H (10 April 2018); doi: 10.1117/12.2303541
Show Author Affiliations
Ning Li, Wuhan Institute of Technology (China)
Hubei Key Lab. of Intelligent Robot (China)
Tongwei Lu, Wuhan Institute of Technology (China)
Hubei Key Lab. of Intelligent Robot (China)
Yanduo Zhang, Wuhan Institute of Technology (China)
Hubei Key Lab. of Intelligent Robot (China)


Published in SPIE Proceedings Vol. 10615:
Ninth International Conference on Graphic and Image Processing (ICGIP 2017)
Hui Yu; Junyu Dong, Editor(s)

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