A framework for efficient correspondence using feature interrelations

We propose a formulation for solving the point pattern correspondence problem, relying on transformation invariants. Our approach can accommodate any degree of descriptors thus modeling any kind of potential deformation according to the needs of each specific problem. Other potential descriptors such as color or local appearance can also be incorporated. A brief study on the complexity of the methodology is made which proves to be inherently polynomial while allowing for further adjustments via thresholding. Initial experiments on both synthetic and real data demonstrate its potentials in terms of accuracy and robustness to noise and outliers.