Pig target tracking algorithm based on multi-channel color feature fusion

Longqing Sun, Shuaihua Chen, Ting Liu, Chunhong Liu, Yan Liu

Abstract


In the process of tracking the target of the pig, with the change of the size of the tracking target in the video image, the estimated tracking target scale cannot be adaptively updated in real-time, resulting in the low accuracy of the tracking target. In this study, a multi-channel color feature adaptive fusion algorithm was proposed, and the target scale of the pig was updated in real-time by utilizing the contour information of the target pig. Experiments show that the proposed algorithm had a distance precision of 89.7% and an overlap precision of 87.5%, and the average running speed of this algorithm was 50.1 fps. The robustness of the proposed algorithm in tracking target deformation and scale variation were significantly improved, which satisfies the accuracy and real-time requirements of pig target tracking.
Keywords: pig tracking, color feature, correlation filter, ellipse fitting
DOI: 10.25165/j.ijabe.20201303.5346

Citation: Sun L Q, Chen S H, Liu T, Liu C H, Liu Y. Pig target tracking algorithm based on multi-channel color feature fusion. Int J Agric & Biol Eng, 2020; 13(3): 180–185.

Keywords


pig tracking, color feature, correlation filter, ellipse fitting

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References


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