| Citation: | GUO Q，WU T H，XU W，et al. Target tracking algorithm based on saliency awareness and consistency constraint[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（9）：2244-2257 （in Chinese） doi: 10.13700/j.bh.1001-5965.2021.0688
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Aimed at the problems that the spatially regularized discriminative correlation filtering (SRDCF) algorithm with fixed regularization weight and model degradation, a correlation filtering tracking algorithm based on saliency awareness and consistency constraint was proposed. Firstly, the histogram of the oriented gradient feature, shallow feature, and the middle feature was extracted to improve the expression ability of the appearance model. Secondly, the regularization weight between the two adjacent frames was associated after the saliency detection algorithm determined the saliency-awareness reference weight of the initial frame.Furthermore, to prevent the degradation of the filter model,the difference between the practical and the scheduled ideal consistency map was minimized and the consistency level was constrained. In addition, a dynamic constraint strategy was proposed to further improve the adaptability of the tracker in complex scenarios. The algorithm is tested on the public OTB2015, TempleColor128, and UAV20L benchmarks. Experimental results show that compared with SRDCF, the proposed algorithm improves the accuracy by 0.108 and the success rate by 0.077 on OTB2015, with a speed of 22.41 frames per second, and has a good real-time effect.
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