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Extraction of building roof contours from LiDAR data using a Markov-random-field-based approach / E. Dos Santos Galvanin in IEEE Transactions on geoscience and remote sensing, vol 50 n° 3 (March 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 3 (March 2012) . - pp 981 - 987 Titre : Extraction of building roof contours from LiDAR data using a Markov-random-field-based approach Type de document : Article/Communication Auteurs : E. Dos Santos Galvanin, Auteur ; A. Dal Poz, Auteur Année de publication : 2012 Article en page(s) : pp 981 - 987 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] algorithme du recuit simulé [Termes IGN] bati [Termes IGN] champ aléatoire de Markov [Termes IGN] détection de contours [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction automatique [Termes IGN] toit Résumé : (Auteur) This paper proposes a method for the automatic extraction of building roof contours from a digital surface model (DSM) by regularizing light detection and ranging (LiDAR) data. The method uses two steps. First, to detect aboveground objects (buildings, trees, etc.), the DSM is segmented through a recursive splitting technique followed by a region-merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. The optimal configuration of building roof contours is found by minimizing the energy function using a simulated annealing algorithm. Experiments carried out with the LiDAR-based DSM show that the proposed method works properly, as it provides roof contour information with approximately 90% shape accuracy and no verified false positives. Numéro de notice : A2012-101 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2163823 Date de publication en ligne : 15/09/2011 En ligne : https://doi.org/10.1109/TGRS.2011.2163823 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31549 [article]

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