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Spin Images and Neural Networks for Efficient Content-Based Retrieval in 3D Object Databases

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2383))

Abstract

We describe a system for querying 3D model databases using the spin image representation as a shape signature for objects depicted as triangular meshes. The spin image representation facilitates the task of aligning the query object with respect to matched models (coarse-grain registration). The main contribution of this work is the introduction of a three-level indexing schema based on artificial neural networks. The indexing schema improves significantly the efficiency in matching query spin images against those stored in the database. Our results are suitable for content-based retrieval in 3D general object databases. A particular application to molecular databases is also presented.

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© 2002 Springer-Verlag Berlin Heidelberg

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de Alarcón, P.A., Pascual-Montano, A.D., Carazo, J.M. (2002). Spin Images and Neural Networks for Efficient Content-Based Retrieval in 3D Object Databases. In: Lew, M.S., Sebe, N., Eakins, J.P. (eds) Image and Video Retrieval. CIVR 2002. Lecture Notes in Computer Science, vol 2383. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45479-9_24

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  • DOI: https://doi.org/10.1007/3-540-45479-9_24

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43899-1

  • Online ISBN: 978-3-540-45479-3

  • eBook Packages: Springer Book Archive

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