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.