End-to-end representation learning for Correlation Filter based tracking Supplementary material
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چکیده
The solution from the previous section can then be used by defining X to be the matrix in RU×U such that Xw = w ? x. It follows that the kernel matrix K belongs to RU×U and the dual variable α is a signal in RU . The key to the correlation filter is that the circulant structure of X enables the solution to be computed efficiently in the Fourier domain. The matrix X has elements X[u, t] = x[u+ t mod m]. Since the matrix X is symmetric, the template w is obtained as cross-correlation
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تاریخ انتشار 2017