The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
The wave kernel signature: A quantum mechanical approach to shape analysis
Abstract
We introduce the Wave Kernel Signature (WKS) for characterizing points on non-rigid three-dimensional shapes. The WKS represents the average probability of measuring a quantum mechanical particle at a specific location. By letting vary the energy of the particle, the WKS encodes and separates information from various different Laplace eigenfrequencies. This clear scale separation makes the WKS well suited for a large variety of applications. Both theoretically and in quantitative experiments we demonstrate that the WKS is substantially more discriminative and therefore allows for better feature matching than the commonly used Heat Kernel Signature (HKS). As an application of the WKS in shape analysis we show results on shape matching.
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Cites
Shape matching and object recognition using shape contexts
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Die gegenw�rtige Situation in der Quantenmechanik
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A Concise and Provably Informative Multi‐Scale Signature Based on Heat Diffusion
Sun, J., Ovsjanikov, M., & Guibas, L. (2009) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2009.01515.x · Cited by 1,450
Shape Classification Using the Inner-Distance
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Schr�dinger, E. (1935) · Die Naturwissenschaften · doi:10.1007/bf01491987 · Cited by 832
Scale-invariant heat kernel signatures for non-rigid shape recognition
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Articulated mesh animation from multi-view silhouettes
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Wang, Y., Sun, Y., Liu, Z., Sarma, S. E., Bronstein, M. M., & Solomon, J. M. (2019) · ACM Transactions on Graphics · doi:10.1145/3326362 · Cited by 7,199
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Qi, C. R., Yi, L., Su, H., & Guibas, L. J. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1706.02413 · Cited by 2,114
Image Matching from Handcrafted to Deep Features: A Survey
Ma, J., Jiang, X., Fan, A., Jiang, J., & Yan, J. (2021) · International Journal of Computer Vision · doi:10.1007/s11263-020-01359-2 · Cited by 990
Geodesic Convolutional Neural Networks on Riemannian Manifolds
Masci, J., Boscaini, D., Bronstein, M. M., & Vandergheynst, P. (2015) · 2015 IEEE International Conference on Computer Vision Workshop (ICCVW) · doi:10.1109/iccvw.2015.112 · Cited by 721
Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid
Tam, G. K. L., Cheng, Z.-Q., Lai, Y.-K., Langbein, F. C., Liu, Y., Marshall, D., Martin, R. R., Sun, X.-F., & Rosin, P. L. (2013) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2012.310 · Cited by 679
Metadata
- Authors
- Aubry, M., Schlickewei, U., & Cremers, D.
- Venue
- 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)
- Publisher
- IEEE
- Published
- 2011-11
- Pages
- 1626-1633
- ISSN
- 2473-9936 (ISSN-L)
- OpenAlex
- W2091791686
- Cited by
- 731
- References
- 26
- FWCI
- 45.89
- Type
- conference paper
- Language
- en
- Open access
- closed
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