IEEE Transactions on Multimedia · 2007 · 85 citations · 25 references
EngineeringImage RetrievalSpin ImagesSpin Image3D Computer VisionImage AnalysisData ScienceImage-based ModelingComputational ImagingSpin Image SignaturesComputational GeometryGeometric ModelingMachine VisionGeometric Feature ModelingComputer ScienceImage SimilarityMedical Image Computing3D Object RecognitionComputer Vision3D Data RepresentationNatural SciencesContent-based Image Retrieval
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Retrieval by content of 3-D models is becoming more and more important due to the advancements in 3-D hardware and software technologies for acquisition, authoring and display of 3-D objects, their ever-increasing availability at affordable costs, and the establishment of open standards for 3-D 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 3-D 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. </para>
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Robert Osada, Thomas Funkhouser, Bernard Chazelle et al. · ACM Transactions on Graphics · 2002 · 1.6K citations