Content-Based Retrieval of 3-D Objects Using Spin Image Signatures

Retrieval by content of 3D models is becoming more and more important due to the advancements in 3D hardware and software technologies for acquisition, authoring and display of 3D objects, their ever-increasing availability at affordable costs, and the establishments of open standards for 3D data interchange. In this paper, we present a new method, referred to as spin image signatures, that develops on the original spin images approach, with adaptations to support effective retrieval by content. According to the method proposed, a set of spin images is derived for each model, to obtain a view-independent description of its 3D shape and a signature is evaluated for each spin image in the set. Clustering is hence performed on the set of spin image signatures to obtain a compact representation. Experimental results are presented, showing the effectiveness of the spin image signatures method for retrieval, also in comparison with other methods, and its sensitivity to model deformations

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