Geometric Feature Estimators for Noisy Discrete Surfaces
Identifieur interne : 004494 ( Main/Merge ); précédent : 004493; suivant : 004495Geometric Feature Estimators for Noisy Discrete Surfaces
Auteurs : L. Provot [France] ; I. Debled-Rennesson [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ]
Abstract
Abstract: We present in this paper robust geometric feature estimators on the border of a possibly noisy discrete object. We introduce the notion of patch centered at a point of this border. Thanks to a width parameter, attached to a patch, the noise on the border of the discrete object can be considered, and an extended flat neighborhood of a border point is computed. Stable geometric features are then extracted around this point. A normal vector estimator is proposed as well as a detector of convex and concave parts on the border of a discrete object.
Url:
- https://api.istex.fr/ark:/67375/HCB-G0HVFB00-C/fulltext.pdf
- https://hal.archives-ouvertes.fr/hal-00345284
DOI: 10.1007/978-3-540-79126-3_25
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<front><div type="abstract" xml:lang="en">Abstract: We present in this paper robust geometric feature estimators on the border of a possibly noisy discrete object. We introduce the notion of patch centered at a point of this border. Thanks to a width parameter, attached to a patch, the noise on the border of the discrete object can be considered, and an extended flat neighborhood of a border point is computed. Stable geometric features are then extracted around this point. A normal vector estimator is proposed as well as a detector of convex and concave parts on the border of a discrete object.</div>
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<front><div type="abstract" xml:lang="en">We present in this paper robust geometric feature estimators on the border of a possibly noisy discrete object. We introduce the notion of patch centered at a point of this border. Thanks to a width parameter, attached to a patch, the noise on the border of the discrete object can be considered, and an extended flat neighborhood of a border point is computed. Stable geometric features are then extracted around this point. A normal vector estimator is proposed as well as a detector of convex and concave parts on the border of a discrete object.</div>
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