RANSAC is the most widely used robust regression algorithm in computer vision.Starting from the Tc,d pre-evaluation model of RANSAC algorithm,a two-step method is presented for optimal (c,d) selection. Based on this method,the adaptive Tc,d test extension is proposed to achieve user independent RANSAC acceleration. We show experimentally that using both short-baseline and wide-baseline epipolar geometry estimation,the proposed method is up to 400% faster than the standard RANSAC.
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