A probabilistic approach for 3D shape retrieval by characteristic views
This work addresses the problem of 3D models retrieval and recognition using two-dimensional shape representation of 3D objects. However, the human perception of shapes is based on visual parts of objects, where a single significant visual part is sufficient to recognize the whole object. In this paper we present a shape similarity system based on the correspondence of visual 2D parts. These parts are obtained by a shape segmentation approach using the Curvature Scale Space (CSS) descriptor in order to solve scale problems. We propose to combine this partial search method with a probabilistic approach. Finally, we propose a 3D search engine based on 3D models characteristic views and a probabilistic Bayesian voting approach.
characteristic views curvature scale space bayesian voting partial shape retrieval m-tree 3d indexing