3D Shape Histograms for Similarity Search and Classification in Spatial Databases
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
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ICCS '07 Proceedings of the 7th international conference on Computational Science, Part II
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ICCS '07 Proceedings of the 7th international conference on Computational Science, Part II
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MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
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ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
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With the advent of the world wide web, the number of available 3D models has increased substantially and the challenge has changed from "How do we generate 3D models?" to "How do we find them?" In this sketch we describe a new 3D model matching and indexing algorithm that uses spherical harmonics to compute discriminating similarity measures without requiring repair of model degeneracies or alignment of orientations. It provides 46-245% better performance than related shape matching methods during precision-recall experiments, and it is fast enough to return query results from a repository of 20,000 models in under half a second.