A boosting approach to content-based 3D model retrieval
Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia
Multiresolution wavelet analysis of shape orientation for 3d shape retrieval
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
A New Shape Benchmark for 3D Object Retrieval
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
A 3D shape retrieval method based on continuous spherical wavelet transform
CGIM '07 Proceedings of the Ninth IASTED International Conference on Computer Graphics and Imaging
Supervised learning of similarity measures for content-based 3D model retrieval
LKR'08 Proceedings of the 3rd international conference on Large-scale knowledge resources: construction and application
International Journal of Computer Vision
3D model search using stochastic attributed relational tree matching
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part II
From 2D silhouettes to 3D object retrieval: contributions and benchmarking
Journal on Image and Video Processing
Exploration of continuous variability in collections of 3D shapes
ACM SIGGRAPH 2011 papers
Graspable parts recognition in man-made 3d shapes
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
ACM Transactions on Graphics (TOG)
CM-BOF: visual similarity-based 3D shape retrieval using Clock Matching and Bag-of-Features
Machine Vision and Applications
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The description of 3D shapes with features that possess descriptive power and invariant under similarity transformations is one of the most challenging issues in content based 3D model retrieval. Spherical harmonics-based descriptors have been proposed for obtaining rotation invariant representations. However, spherical harmonic analysis is based on latitude-longitude parameterization of a sphere which has singularities at each pole. Consequently, features near the two poles are over represented while features at the equator are under-sampled, and variations of the north pole affects significantly the shape function. In this paper we discuss these issues and propose the usage of spherical wavelet transform as a tool for the analysis of 3D shapes represented by functions on the unit sphere. We introduce three new descriptors extracted from the wavelet coefficients, namely: (1) a subset of the spherical wavelet coefficients, (2) the L1 and, (3) the L2 energies of the spherical wavelet sub-bands. The advantage of this tool is three fold; First, it takes into account feature localization and local orientations. Second, the energies of the wavelet transform are rotation invariant. Third, shape features are uniformly represented which makes the descriptors more efficient. Spherical wavelet descriptors are natural extension of 3D Zernike moments and spherical harmonics. We evaluate, on the Princeton Shape Benchmark, the proposed descriptors regarding computational aspects and shape retrieval performance.