10 April 2018 Object tracking algorithm based on the color histogram probability distribution
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Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 106150H (2018) https://doi.org/10.1117/12.2303541
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China
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.
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Ning Li, Ning Li, Tongwei Lu, Tongwei Lu, Yanduo Zhang, Yanduo Zhang, } "Object tracking algorithm based on the color histogram probability distribution", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106150H (10 April 2018); doi: 10.1117/12.2303541; https://doi.org/10.1117/12.2303541
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