A global-to-local scheme for imbalanced point matching

Imbalanced points are image points whose first-order intensity can be clustered into two imbalanced classes. An important property of imbalanced points is that they can be contiguous to each other. The property helps improve the localization accuracy of imbalanced points across imaging variations. Based on this local geometric coherency property, we propose a global-to-local scheme for imbalanced point matching. The proposed matching scheme first builds correspondence between components of coherent imbalanced points and then refines point correspondence within corresponding components. We test the global-to-local matching scheme, compared with several other well-known methods, on a set of groundtruth stereo images. Furthermore, we present a case study of the proposed scheme in face liveness detection. Our results show the promise of the global-to-local matching scheme.