Visual Assessments of Functional Maps

Abstract

Shape-matching is one central topic in Geometry Processing, with numerous important applications in Computer Graphics and shape analysis, such as shape registration, shape interpolation, modeling, information transfer and many others. A recent and successful class of shape-matching methods is based on the functional maps framework [OBCS*12] where the correspondences between the two surfaces is described in terms of a mapping between functions. Several effective approaches have been proposed to produce accurate and reliable functional maps, leading to need for a way to assess the quality of a given solution. In particular, standard quantitative evaluation methods focus mainly on the global matching error disregarding the annoying effects of wrong correspondences along the surface details. Therefore, in this context, it is very important to pair quantitative numeric evaluations with a visual, qualitative assessment. Although this is usually not recognized as a problem, the latter task is not trivial, and we argue that the commonly employed solutions suffer from important limitations. In this work, we offer a new visual evaluation method which is based on the transfer of the object-space normals across the two spaces and then visualize the resulting lighting. In spite of its simplicity, this method produces readable images that allow subtleties of the mapping to be discerned, and improve direct comparability of alternative results.