Robust point correspondence by concave minimization

摘要

We propose a new methodology for reliably solving the correspondence problem between points of two or more images. This is a key step in most problems of Computer Vision and, so far, no general method exists to solve it. Our methodology is able to handle most of the commonly used assumptions in a unique formulation, independent of the domain of Application and type of features. It performs correspondence and outlier rejection in a single step, and achieves global optimality with feasible Computation. Feature selection and correspondence are first formulated as an integer optimization problem.