Thesaurus-based 3D Object Retrieval with Part-in-Whole Matching
- 276 Downloads
Research in content-based 3D retrieval has already started, and several approaches have been proposed which use in different manner a similarity assessment to match the shape of the query against the shape of the objects in the database. However, the success of these solutions are far from the success obtained by their textual counterparts.
A major drawback of most existing 3D retrieval solutions is their inability to support partial queries, that is, a query which does not need to be formulated by specifying a whole query shape, but just a part of it, for example a detail of its overall shape, just like documents are retrieved by specifying words and not whole texts. Recently, researchers have focused their investigation on 3D retrieval which is solved by partial shape matching. However, at the extent of our knowledge, there is still no 3D search engine that provides an indexing of the 3D models based on all the interesting subparts of the models.
In this paper we present a novel approach to 3D shape retrieval that uses a collection-aware shape decomposition combined with a shape thesaurus and inverted indexes to describe and retrieve 3D models using part-in-whole matching. The proposed method clusters similar segments obtained trough a multilevel decomposition of models, constructing from such partition the shape thesaurus. Then, to retrieve a model containing a sub-part similar to a given query, instead of looking on a large set of subparts or executing partial matching between the query and all models in the collection, we just perform a fast global matching between the query and the few entries in the thesaurus. With this technique we overcame the time complexity problems associated with partial queries in large collections.
Keywords3D shape retrieval Part-in-whole matching Thesaurus Segmentation
Unable to display preview. Download preview PDF.
- Agathos, A., Pratikakis, I., Perantonis, S., Sapidis, N., & Azariadis, P. (2007). 3D mesh segmentation methodologies for cad applications. Computer-Aided Design and Applications, 4(6), 827–841. Google Scholar
- Ansary, T. F., Daoudi, M., & Vandeborre, J. P. (2007b). 3d-models search engine from photos. In Proceedings of ACM international conference on image and video retrieval (CIVR 2007). Amsterdam, The Netherlands. Google Scholar
- Attene, M. (2006). ‘efpisoft’. http://efpisoft.sourceforge.net/
- Baeza-Yates, R. A., & Ribeiro-Neto, B. (1999). Modern Information Retrieval. Reading: Addison-Wesley. Google Scholar
- Cormack, G. V., Palmer, C. R., & Clarke, C. L. A. (1998). Efficient construction of large test collections. In SIGIR’98: proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval (pp. 282–289). New York: ACM. http://doi.acm.org/10.1145/290941.291009 CrossRefGoogle Scholar
- Cornea, N. D., Demirci, M. F., Silver, D., Shokoufandeh, A., Dickinson, S. J., & Kantor, P. B. (2005). 3d object retrieval using many-to-many matching of curve skeletons. In SMI’05: proceedings of the international conference on shape modeling and applications 2005 (pp. 368–373). Los Alamitos: IEEE Computer Society. Google Scholar
- Fonseca, M. J., & Jorge, J. A. (2003). Indexing high-dimensional data for content-based retrieval in large databases. In Proceedings of the 8th international conference on database systems for advanced applications (DASFAA’03) (pp. 267–274). Los Alamitos: IEEE Computer Society. Google Scholar
- Joyce, T., & Needham, R. M. (1997). The thesaurus approach to information retrieval. Readings in information retrieval, pp. 15–20. Google Scholar
- Kazhdan, M. (2004). Shape representation and algorithms for 3d model retrieval. Ph.D. thesis, Princeton University. Google Scholar
- Kazhdan, M., Funkhouser, T., & Rusinkiewicz, S. (2003). Rotation invariant spherical harmonic representation of 3d shape descriptors. In L. Kobbelt, P. Schroder, & H. Hoppe (Eds.), Proceedings of the 2003 eurographics/ACM SIGGRAPH symposium on geometry processing (pp. 156–164). Aire-la-Ville: Eurographics Association. Google Scholar
- Lou, K., Prabhakar, S., & Ramani, K. (2004). Content-based three-dimensional engineering shape search. International conference on data engineering, p. 754. Google Scholar
- Milne, D. N., Witten, I. H., & Nichols, D. M. (2007). A knowledge-based search engine powered by wikipedia. In CIKM’07: proceedings of the sixteenth ACM conference on conference on information and knowledge management (pp. 445–454). New York: ACM. http://doi.acm.org/10.1145/1321440.1321504. CrossRefGoogle Scholar
- Paquet, E., & Rioux, M. (1997). Nefertiti: A query by content software for three-dimensional models databases management. 3dim, p. 345. Google Scholar
- Suzuki, M. T., Kato, T., & Otsu, N. (2000). A similarity retrieval of 3d polygonal models using rotation invariant shape descriptors. In Proceedings of IEEE international conference on systems, man and cybernetics (Vol. 4, pp. 2946–2952). Los Alamitos: IEEE Computer Society. Google Scholar
- Suzuki, M. T., Yaginuma, Y., & Sugimoto, Y. Y. (2003). A 3d model retrieval system for cellular phones. In Proceedings of IEEE international conference on systems, man and cybernetics (Vol. 4, pp. 3846–3851). Los Alamitos: IEEE Computer Society. Google Scholar
- Suzuki, M. T., Yaginuma, Y., Yamada, T., & Shimizu, Y. (2005a). A partial shape matching method for 3d model databases. In Proceedings of the ninth IASTED international conference on software engineering and applications (SEA2005) (pp. 389–394). Calgary: ACTA Press. Google Scholar
- Vranić, D. V. (2004). 3d model retrieval. Ph.D. thesis, University of Leipzig, Germany. Google Scholar