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This paper introduces a tuning algorithm of self-quotient ε-filter (SQEF) and support vector machine (SVM), and its application to noise robust human detection combining SQEF, histograms of oriented gradients (HOG), and SVM. Although human detection combining HOG and SVM is a powerful approach, as it uses local intensity gradients, it is difficult to handle noise corrupted images. On the other hand, although human detection combining SQEF, HOG and SVM can realize noise robust human detection, SQEF requires manual parameter setting. Our aim is not only to set the parameter of self-quotient e-filter but also to train SVM by using numerous images without noise and a small amount of images with noise.