Is there an easy way/algorithm to match 2 clouds of 2D points?

Question

I am wondering if there is an easy way to match (register) 2 clouds of 2d points.

Let\'s say I have an object represented by points and an cluttered 2nd image with t

Answer 1

Let me first make sure I'm interpreting your question correctly. You have two sets of 2D points, one of which contains all "good" points corresponding to some object of interest, and one of which contains those points under an affine transformation with noisy points added. Right?

If that's correct, then there is a fairly reliable and efficient way to both reject noisy points and determine the transformation between your points of interest. The algorithm that is usually used to reject noisy points ("outliers") is known as RANSAC, and the algorithm used to determine the transformation can take several forms, but the most current state of the art is known as the five-point algorithm and can be found here -- a MATLAB implementation can be found here.

Unfortunately I don't know of a mature implementation of both of those combined; you'll probably have to do some work of your own to implement RANSAC and integrate it with the five point algorithm.

Edit:

Actually, OpenCV has an implementation that is overkill for your task (meaning it will work but will take more time than necessary) but is ready to work out of the box. The function of interest is called cv::findFundamentalMat.