Combining Topological and Geometrical Features for Global and Partial 3-D Shape Retrieval
| Autor: | Apostolos Axenopoulos, Petros Daras, M.G. Strintzis, A. Mademlis, Dimitrios Tzovaras |
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| Rok vydání: | 2008 |
| Předmět: |
Superellipsoid
Matching (graph theory) Computer science business.industry Cognitive neuroscience of visual object recognition Graph theory Pattern recognition Graph Similitude Computer Science Applications Signal Processing Media Technology Graph (abstract data type) Artificial intelligence Electrical and Electronic Engineering business Distance transform Image retrieval |
| Zdroj: | IEEE Transactions on Multimedia. 10:819-831 |
| ISSN: | 1941-0077 1520-9210 |
| DOI: | 10.1109/tmm.2008.922790 |
| Popis: | This paper presents a novel framework for 3-D object content-based search and retrieval, appropriate for both partial and global matching applications. The framework is based on a graph representation of a 3-D object which is enhanced by local geometric features. The 3-D object is decomposed into meaningful parts and an attributed graph is constructed based on the connectivity of the parts. Every 3-D part is approximated with a suitable superellipsoid and a novel 3-D shape descriptor, called a 3-D distance field descriptor, is computed and associated to the corresponding graph nodes. The matching process used is based on attributed graph matching algorithm appropriate for this application. The proposed method not only provides successful retrieval results in terms of geometric similarity but also is invariant to rotation, translation and scaling of an object as well as to the different poses of articulated objects. Finally, it can be effectively used for partial and global 3-D object retrieval. |
| Databáze: | OpenAIRE |
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