Surface partial matching and application to archaeology

Partial matching is a fundamental problem in shape analysis, a field that is recently gaining an increasing importance in computer graphics. This paper proposes a novel approach to performing partial matching of surfaces. Given two surfaces M_A and M_B, our goal is to find the best match to M_A within M_B. The key idea of our approach is to integrate feature-point similarity and segment similarity. Specifically, we introduce a probabilistic framework in which the segmentation and the correspondences of neighboring feature points allow us to enhance or moderate our certainty of a feature-point similarity. The utility of our algorithm is demonstrated in the domain of archaeology, where digital archiving is becoming ever more widespread. In this domain, automatic matching can serve as a worthy alternative to the expensive and time-consuming manual procedure that is used today.