The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
The power crust
Abstract
The power crust is a construction which takes a sample of points from the surface of a three-dimensional object and produces a surface mesh and an approximate medial axis. The approach is to first approximate the medial axis transform (MAT) of the object. We then use an inverse transform to produce the surface representation from the MAT.This idea leads to a simple algorithm with theoretical guarantees comparable to those of other surface reconstruction and medial axis approximation algorithms. It also comes with a guarantee that does not depend in any way on the quality of the input point sample. Any input gives an output surface which is the `watertight' boundary of a three-dimensional polyhedral solid: the solid described by the approximate MAT. This unconditional guarantee makes the algorithm quite robust and eliminates the polygonalization, hole-filling or manifold extraction post-processing steps required in previous surface reconstruction algorithms.In this paper, we use the theory to develop a power crust implementation which is indeed robust for realistic and even difficult samples. We describe the careful design of a key subroutine which labels parts of the MAT as inside or outside of the object, easy in theory but non-trivial in practice. We find that we can handle areas in which the input sampling is scanty or noisy by simply discarding the unreliable parts of the MAT approximation. We demonstrate good empirical results on inputs including models with sharp corners, sparse and unevenly distributed point samples, holes, and noise, both natural and synthetic.We also demonstrate some simple extensions: intentionally leaving holes where there is no data, producing approximate offset surfaces, and simplifying the approximate MAT in a principled way to preserve stable features.
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Cited by
Surmann, H., Nüchter, A., & Hertzberg, J. (2003) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2003.09.004 · Cited by 527
3D reconstruction methods for digital preservation of cultural heritage: A survey
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Retrieving articulated 3-D models using medial surfaces
Siddiqi, K., Zhang, J., Macrini, D., Shokoufandeh, A., Bouix, S., & Dickinson, S. (2008) · Machine Vision and Applications · doi:10.1007/s00138-007-0097-8 · Cited by 256
Automatic animation skeleton using repulsive force field
Liu, P.-C., Wu, F.-C., Ma, W.-C., Liang, R.-H., & Ouhyoung, M. (2004) · 11th Pacific Conference onComputer Graphics and Applications, 2003. Proceedings. · doi:10.1109/pccga.2003.1238285 · Cited by 57
3D model reconstruction using neural gas accelerated on GPU
Orts-Escolano, S., Garcia-Rodriguez, J., Serra-Perez, J. A., Jimeno-Morenilla, A., Garcia-Garcia, A., Morell, V., & Cazorla, M. (2015) · Applied Soft Computing · doi:10.1016/j.asoc.2015.03.042 · Cited by 8
Metadata
- Authors
- Amenta, N., Choi, S., & Kolluri, R. K.
- Venue
- Proceedings of the sixth ACM symposium on Solid modeling and applications
- Publisher
- ACM
- Published
- 2001-05
- Pages
- 249-266
- OpenAlex
- W2020065037
- Cited by
- 721
- References
- 27
- FWCI
- 63.81
- Type
- conference paper
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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