Semantics-driven best view of 3D shapes

The problem of automatically selecting the pose of a 3D object that corresponds to the most informative and intuitive view of the shape is known as the best view problem. In this paper we address the selection of the best view driven by the meaningful features of the shape, in order to maximize the visibility of salient components from the context or from the application point of view. Meaningful features can be automatically detected by means of semantic-oriented segmentations: we tested several approaches with very pleasant results in the automatic generation of thumbnails for large 3D model databases.