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Automated detection of branch dimensions in woody skeletons of fruit tree canopies / Alexander Bucksch in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 3 (March 2011)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 77 n° 3 (March 2011) . - pp 229 - 240 Titre : Automated detection of branch dimensions in woody skeletons of fruit tree canopies Type de document : Article/Communication Auteurs : Alexander Bucksch, Auteur ; Stefan Fleck, Auteur Année de publication : 2011 Conférence : SilviLaser 2010, 10th International Conference on LiDAR Applications for Assessing Forest Ecosystems 14/09/2010 17/09/2010 Fribourg Allemagne Article en page(s) : pp 229 - 240 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre (flore) [Termes IGN] branche (arbre) [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] houppier [Termes IGN] semis de points [Termes IGN] SKELTRE algorithm [Termes IGN] squelettisation Résumé : (auteur) Modeling the 3D canopy structure of trees provides the structural mapping capability on which to assign distributed values of light-driven physiological processes in tree canopies. We evaluate the potential of automatically extracted skeletons from terrestrial lidar data as a basis for modeling canopy structure. The automatic and species independent evaluation method for lidar data of trees is based on the SKELTRE algorithm. The SKELTRE skeleton is a graphical representation of the branch hierarchy. The extraction of the branch hierarchy utilizes a graph splitting procedure to extract the branches from the skeleton. Analyzing the distance between the point cloud points and the skeleton is the key to the branch diameter. Frequency distributions of branch length and diameter were chosen to test the algorithm performance in comparison to manually measured data and resulted in a correlation of up to 0.78 for the branch length and up to 0.99 for the branch diameter. Numéro de notice : A2011-157 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.77.3.229 En ligne : https://doi.org/10.14358/PERS.77.3.229 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81267 [article]

CAMPINO, a skeletonization method for point cloud processing / Alexander Bucksch in ISPRS Journal of photogrammetry and remote sensing, vol 63 n° 1 (January - February 2008)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 63 n° 1 (January - February 2008) . - pp 115 - 127 Titre : CAMPINO, a skeletonization method for point cloud processing Type de document : Article/Communication Auteurs : Alexander Bucksch, Auteur ; R. Linderberg, Auteur Année de publication : 2008 Article en page(s) : pp 115 - 127 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] balayage laser [Termes IGN] segmentation d'image [Termes IGN] semis de points [Termes IGN] squelettisation [Termes IGN] télémètre laser terrestre [Termes IGN] traitement géométrique de données [Termes IGN] végétation Résumé : (Auteur) A new algorithm for deriving skeletons and segmentations from point cloud data in O(n) time is explained in this publication. This skeleton is represented as a graph, which can be embedded into the point cloud. The CAMPINO method, (C)ollapsing (A)nd (M)erging (P)rocedures (IN) (O)ctree-graphs, is based on cycle elimination in a graph as derived from an octree based space division procedure. The algorithm is able to extract the skeleton from point clouds generated from either one or multiple viewpoints. The correspondence between the vertices of the graph and the original points of the point cloud is used to derive an initial segmentation of these points. The principle of the algorithm is demonstrated on a synthetic point cloud consisting of 3 connected tori. Initially this algorithm was developed to obtain skeletons from point clouds representing natural trees, measured with the terrestrial laser scanner IMAGER 5003 of Zoller+Fröhlich. The results show that CAMPINO is able to automatically derive realistic skeletons that fit the original point cloud well and are suited as a basis for e.g. further automatic feature extraction or skeleton-based registration. Copyright ISPRS Numéro de notice : A2008-040 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2007.10.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2007.10.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29035 [article]

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