Corpus ID: 11965632

Spectral descriptors for deformable shapes

@article{Bronstein2011SpectralDF,
  title={Spectral descriptors for deformable shapes},
  author={Alexander M. Bronstein},
  journal={ArXiv},
  year={2011},
  volume={abs/1110.5015}
}
  • Alexander M. Bronstein
  • Published in ArXiv 2011
  • Computer Science, Mathematics
  • Informative and discriminative feature descriptors play a fundamental role in deformable shape analysis. For example, they have been successfully employed in correspondence, registration, and retrieval tasks. In the recent years, significant attention has been devoted to descriptors obtained from the spectral decomposition of the Laplace-Beltrami operator associated with the shape. Notable examples in this family are the heat kernel signature (HKS) and the wave kernel signature (WKS). Laplacian… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 35 REFERENCES

    The wave kernel signature: A quantum mechanical approach to shape analysis

    VIEW 9 EXCERPTS
    HIGHLY INFLUENTIAL

    Diffusion maps

    • R. Coifman, S. Lafon
    • Applied and Computational Harmonic Analysis, vol. 21, no. 1, pp. 5–30, 2006.
    • 2006
    VIEW 3 EXCERPTS
    HIGHLY INFLUENTIAL

    LDAHash: Improved Matching with Smaller Descriptors

    VIEW 1 EXCERPT

    Persistence-based segmentation of deformable shapes

    VIEW 1 EXCERPT

    Scale-invariant heat kernel signatures for non-rigid shape recognition

    VIEW 2 EXCERPTS