Surface point signatures for free-form object registration and recognition

This thesis introduces a new free-form surface representation scheme for the purpose of fast and accurate registration and object matching under any similarity transformation. Accurate registration of surfaces is a common task in computer vision. The proposed representation scheme captures the surface curvature information, seen from certain points and produces images, called surface. signatures, at these points. Matching signatures of different surfaces enables the recovery of the transformation parameters between these surfaces. We propose to use template matching to compare the signature images. To enable partial matching, another criterion, the overlap ratio, is used. This representation scheme can be used as a global representation of the surface as well as a local one and performs near real-time registration. The representation is the first to perform scale independent 3-D matching, a problem that was not addressed in currently existing registration techniques. We show that the signature representation can be used to match objects in 3-D scenes in the presence of clutter and occlusion. Applications presented include free-form object matching and medical volumes registration.