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Visual target tracking is one of fundamental research of computer vision field and play an important role in the surveillance application, but it is also one of the difficulties due to the instability of the tracking scene. In this paper, we analyze the major drawbacks of the original Kernelized Correlation Filter (KCF) tracker which causes tracking failure when target experience complicated scenarios...
Original signal is decomposed by wavelet in different scales, the wavelet decomposition coefficients of the real signal are held, and the wavelet decomposition coefficients of the noise are eliminated, then the signal is reconstructed by inverse wavelet transform. Kernel PCA can eliminate the relativity of variables and extract the fault information better, the feature information of the pretreatment...
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