Spin images for retrieval of 3D objects by local and global similarity
Jürgen Assfalg, Alberto Del Bimbo, Pietro Pala · Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. · 2004
The ever increasing availability of 3D models demands for tools supporting their effective and efficient management. Among these tools, those enabling content-based retrieval play a key role. In this paper, we present a novel approach to global and local content-based retrieval of 3D objects that is based on spin images. Spin images are used to derive a view-independent description of both database and query objects. A set of spin images is first created for each object and the parts it is composed of; then, a descriptor is evaluated for each spin image in the set; clustering is performed on the set of image-based descriptors of each object to achieve a compact representation. Experimental results are presented for a test database of about 300 models, showing the effectiveness of retrieval for both object and part similarity.