Object tracking algorithm based on the color histogram probability distribution

Ning Li; Tongwei Lu; Yanduo Zhang

doi:10.1117/12.2303541

10 April 2018 Object tracking algorithm based on the color histogram probability distribution

Ning Li, Tongwei Lu, Yanduo Zhang

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.

Citation Download Citation

Ning Li, Tongwei Lu, and 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); https://doi.org/10.1117/12.2303541

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KEYWORDS

Target detection

Detection and tracking algorithms

RGB color model

Filtering (signal processing)

Sensors

Motion models

Iterative methods

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