Performance Evaluation of Robust Matching Measures

This paper is aimed at evaluating the performances of different measures which have been proposed in literature for robust matching. In particular, classical matching metrics typically employed for this task are considered together with specific approaches aiming at achieving robustness. The main aspects assessed by the proposed evaluation are robustness with respect to photometric distortions, noise and occluded patterns. Specific datasets have been used for testing, which provide a very challenging framework for what concerns the considered disturbance factors and can also serve as testbed for evaluation of future robust visual correspondence measures.