High-Speed Tracking with Kernelized Correlation Filters

Linear regression f(z)=wTz minwΣi(f(xi)−yi)2+λ||w||2 w=(XTX+λI)−1XTy w∗=(XHX+λI)−1XHy Circulant matrices X=FHdiag(x^)F x^=F(x) xi in linear regression corresponds to a vector x=[x1,...,xn] So, we can

>>阅读原文<<