Surface Matching

3D biometrics work by computing the similarity between 3D surfaces of objects belonging to the same class. The majority of the techniques used measure the similarity among homologous salient geometric features on the surfaces (e.g. based on curvature). The localization of these features is usually based on prior knowledge of the surface class (e.g. face, hand) and thus, specialized feature detectors may be used. The geometric attributes extracted are selected so that they are invariant to transformations such as rotation, translation and scaling. In the case that knowledge-based feature detection is difficult, a correspondence among the surfaces may be established by randomly selecting points on the two surfaces and then trying to find pairs of points with similar geometric attributes. Several such techniques have been developed for rigid surface matching (e.g. Spin Images) which may be extended for matching non-rigid or articulated surfaces. Another technique for establishing...