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Robust visual tracking with spatial phase correlation

机译:具有空间相位相关性的强大视觉跟踪

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摘要

The visual tracker based on phase correlation is always failure, because the response is dirac δ function disturbed by the noise and clutter. Recently, the desired correlated output distribution is adopted in ASEF, which obtains the excellent filtered result. Inspired by the above method, spatial phase correlation is proposed in this paper, which designs the response related with the object spatial position to replace the dirac δ function, which can achieve a robust filter. The phase difference is embedded into the response frequency spectrum to obtain the coarse location of the object. Then the phase saliency is exploited to finely track the object for the excellent performance. To avoid the drifting problem, adaptive template is updated by the peak-sidelobe ratio(PSR), which evaluates the tracking results. Numerical experiments show that the proposed algorithm performs favorably against the state-of-the-art trackers in speed, accuracy and robustness.
机译:基于相位相关性的视觉跟踪器总是失败,因为响应是受噪声和杂波干扰的狄拉克δ函数。最近,在ASEF中采用了所需的相关输出分布,从而获得了出色的滤波结果。受上述方法的启发,提出了空间相位相关性,设计了与物体空间位置有关的响应,以取代狄拉克δ函数,从而实现了鲁棒的滤波。将相位差嵌入到响应频谱中以获得对象的粗略位置。然后利用相位显着性对对象进行精细跟踪以获得出色的性能。为了避免漂移问题,自适应模板通过峰旁瓣比(PSR)更新,该模板评估跟踪结果。数值实验表明,所提出的算法在速度,准确性和鲁棒性方面均优于最新的跟踪器。

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