ACM Transactions on Graphics (TOG)
3D Shape Histograms for Similarity Search and Classification in Spatial Databases
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Rotation invariant spherical harmonic representation of 3D shape descriptors
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
SMI '04 Proceedings of the Shape Modeling International 2004
Feature Combination and Relevance Feedback for 3D Model Retrieval
MMM '05 Proceedings of the 11th International Multimedia Modelling Conference
3D model retrieval based on multi-shell extended Gaussian image
VISUAL'07 Proceedings of the 9th international conference on Advances in visual information systems
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In this paper, we propose a novel shape descriptor for 3D objects, called spatial geometric descriptor (SGD), to represent the spatial geometric information of a 3D model by mapping its furthest distance, normal and area distribution onto spherical grids in a sequence of concentric shells. Then these spherical distribution functions are transformed to spherical harmonic coefficients which not only save the storage space but also provide multi-resolution shape description for any 3D model by adopting different dimensions for the coefficients. The feature vector extraction time can be reduced by adopting a single scan scheme on the mesh surface for a given 3D model. The retrieval performance is evaluated on the public Princeton Shape Benchmark (PSB) dataset and the experimental results show that our method not only outperforms Light Field Descriptor which is regarded as the best shape descriptor so far but also maintains an advantage of fast feature vector extraction procedure.