Context-adaptive navigation of 3D model collections

Abstract

When reasoning about similarity in a collection of objects with heterogeneous qualities, there are several aspects of interest that can be followed to explore the collection. Indeed, the notion of similarity among 3D models is not only grounded on the geometric shape but also, for instance, on the style, material, color, decorations, common parts. These are all important factors that concur to the concept of similarity. Search engines for visual content are expected to address similarity assessment in collections, providing a higher degree of flexibility with respect to the traditional 3D object retrieval operations. In this work, we describe the design and functioning of a search engine working on multiple factors and discuss the results on a number of collections, which challenge existing 3D object retrieval engines.