This paper presents the methods that have participated in the SHREC'20 contest on retrieval of surface patches with similar geometric reliefs and 1 the analysis of their performance over the benchmark created for this challenge. The goal of the context is to verify the possibility of retrieving 3D models only based on the reliefs that are present on their surface and to compare methods that are suitable for this task. This problem is related to many real world applications, such as the classification of cultural heritage goods or the analysis of different materials. To address this challenge, it is necessary to characterize the local "geometric pattern" information, possibly forgetting model size and bending. Seven groups participated in this contest and twenty runs were submitted for evaluation. The performances of the methods reveal that good results are achieved with a number of techniques that use different approaches.
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.
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