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Efficient and robust reconstruction of botanical branching structure from laser scanned points

Dong-Ming Yan 1 Julien Wintz 2 Bernard Mourrain 2 Wenping Wang 3 Frédéric Boudon 4, 5 Christophe Godin 4, 5
1 CAD - Computer Aided Design
LIAMA - Laboratoire Franco-Chinois d'Informatique, d'Automatique et de Mathématiques Appliquées, Inria Paris-Rocquencourt
2 GALAAD - Geometry, algebra, algorithms
CRISAM - Inria Sophia Antipolis - Méditerranée , UNS - Université Nice Sophia Antipolis (... - 2019), CNRS - Centre National de la Recherche Scientifique : UMR6621
4 VIRTUAL PLANTS - Modeling plant morphogenesis at different scales, from genes to phenotype
CRISAM - Inria Sophia Antipolis - Méditerranée , INRA - Institut National de la Recherche Agronomique, UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales
Abstract : This paper presents a reconstruction pipeline for recovering branching structure of trees from laser scanned data points. The process is made up of two main blocks: segmentation and reconstruction. Based on a variational k-means clustering algorithm, cylindrical components and ramified regions of data points are identified and located. An adjacency graph is then built from neighborhood information of components. Simple heuristics allow us to extract a skeleton structure and identify branches from the graph. Finally, a B-spline model is computed to give a compact and accurate reconstruction of the branching system.
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Contributor : Bernard Mourrain Connect in order to contact the contributor
Submitted on : Thursday, November 26, 2009 - 6:39:43 PM
Last modification on : Friday, October 8, 2021 - 4:26:28 PM
Long-term archiving on: : Tuesday, October 16, 2012 - 3:01:57 PM


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  • HAL Id : inria-00436480, version 1


Dong-Ming Yan, Julien Wintz, Bernard Mourrain, Wenping Wang, Frédéric Boudon, et al.. Efficient and robust reconstruction of botanical branching structure from laser scanned points. CAD/Graphics 2009, Aug 2009, Yellow Mountain City, China. pp.572-575. ⟨inria-00436480⟩



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