Completion of cultural heritage objects with rotational symmetry

Archaeological artifacts are an important part of our cultural heritage. They help us understand how our ancestors used to live. Unfortunately, many of these objects are badly damaged by the passage of time and need repair. If the object exhibits some form of symmetry, it is possible to complete the missing regions by replicating existing parts of the object. In this paper, we present a framework to complete 3D objects that exhibit rotational symmetry. Our approach combines a number of algorithms from the computer vision community that have had good performance at solving similar problems. In order to complete an archaeological artifact, we begin by scanning the object to produce a 3D mesh of triangles. We then preprocess the mesh to remove fissures and smoothen the surface. We continue by detecting the most salient vertices of the mesh (the key-points). If the object exhibits rotational symmetry, the key-points should form a circular structure which the Random Sample Consensus (RANSAC) algorithm should be able to detect. The axis of symmetry of the circle found should correspond to the axis of symmetry of the object. Thus, by rotating the mesh around the axis of the circle we should be able to complete a large portion of the missing regions. We alleviate any misalignment caused during the rotations via a non-rigid alignment procedure. In the evaluation, we compare the performance of our approach with other state of the art algorithms for 3D object completion. The benchmark proves that our algorithm is effective at completing damaged archaeological objects.