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I don't think RANSAC is a good idea in your case. RANSAC can be used when you have a number of measurements (e.g. pairs of corresponding points from 2 sets) containing some outliers (e.g. incorrectly matched points). The more outliers you have the more RANSAC iterations are needed to estimate parameters with a given confidence. In your scenario, choosing matching points randomly, you'll need a really HUGE number of iterations to ensure proper matching is found. Computational cost may be prohibitive.
Can you give more details about your problem. Why are you trying to estimate perspective transform? Are these 2D points projections of some 3D points?
