Retrieval of 3D Polygonal Objects Based on Multiresolution Signatures

Abstract

Abstract. In this paper we present a method for retrieving 3D polygonal objects by using two sets of multiresolution signatures. Both sets are based on the progressive elimination of object's details by iterative processing of the 3D meshes. The first set, with five parameters, is based on mesh smoothing. This mainly affects an object's surface. The second set, with three parameters, is based on difference volumes after successive mesh erosions and dilations. Characteristic feature vectors are constructed by combining the features at three mesh resolutions of each object. In addition to being invariant to mesh resolution, the feature vectors are invariant to translation, rotation and size of the objects. The method was tested on a set of 40 complex objects with mesh resolutions different from those used in constructing the feature vectors. By using all eight features, the average ranking rate obtained was 1.075: 37 objects were ranked first and only 3 objects were ranked second. Additional tests were carried out to determine the significance of individual features and all combinations. The same ranking rate of 1.075 can be obtained by using some combinations of only three features.

Cortical 3D Face and Object Recognition Using 2D Projections

“…For the recognition of general 3D objects, there are also several approaches which have been explored. Some of these are based on 3D shape retrieval methods (Tangelder & Veltkamp, 2008), on 2D projected images (Su et al, 2006) and on multiresolution signatures (Lam & du Buf, 2011), including approaches that can be applied both to 3D objects and to faces (Passalis et al, 2007).…”