Reverse Engineering Methods for Digital Restoration Applications

Abstract

In this paper we discuss the challenges of processing and converting 3D scanned data to representations suitable for interactive manipulation in the context of virtual restoration applications. We present a constrained parametrization approach that allows us to represent 3D scanned models as parametric surfaces defined over polyhedral domains. A combination of normal- and spatial-based clustering techniques is used to generate a partition of the model into regions suitable for parametrization. Constraints can be optionally imposed to enforce a strict correspondence between input and output features. We consider two types of virtual restoration methods: (a) a paint restoration method that takes advantage of the normal-based coarse partition to identify large regions of reduced metric distortion suitable for texture mapping and (b) a shape restoration approach that relies on a refined partition used to convert the input model to a multiresolution subdivision representation suitable for intuitive interactive manipulation during digital studies of historical artifacts.