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A derivative-free optimization-based approach for detecting architectural symmetries from 3D point clouds / Fan Xue in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 148 (February 2019) . - pp 32 - 40 Titre : A derivative-free optimization-based approach for detecting architectural symmetries from 3D point clouds Type de document : Article/Communication Auteurs : Fan Xue, Auteur ; Weisheng Lu, Auteur ; Christopher J. Webster, Auteur ; Ke Chen, Auteur Année de publication : 2019 Article en page(s) : pp 32 - 40 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] détection [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] indice de symétrie [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] modèle 3D de l'espace urbain [Termes descripteurs IGN] octree [Termes descripteurs IGN] programmation non linéaire [Termes descripteurs IGN] semis de points Résumé : (Auteur) Symmetry is ubiquitous in architecture, across both time and place. Automated architectural symmetry detection (ASD) from a data source is not only an intriguing inquiry in its own right, but also a step towards creation of semantically rich building and city information models with applications in architectural design, construction management, heritage conservation, and smart city development. While recent advances in sensing technologies provide inexpensive yet high-quality architectural 3D point clouds, existing methods of ASD from these data sources suffer several weaknesses including noise sensitivity, inaccuracy, and high computational loads. This paper aims to develop a novel derivative-free optimization (DFO)-based approach for effective ASD. It does so by firstly transforming ASD into a nonlinear optimization problem involving architectural regularity and topology. An in-house ODAS (Optimization-based Detection of Architectural Symmetries) approach is then developed to solve the formulated problem using a set of state-of-the-art DFO algorithms. Efficiency, accuracy, and robustness of ODAS are gauged from the experimental results on nine sets of real-life architectural 3D point clouds, with the computational time for ASD from 1.4 million points only 3.7 s and increasing in a sheer logarithmic order against the number of points. The contributions of this paper are threefold. Firstly, formulating ASD as a nonlinear optimization problem constitutes a methodological innovation. Secondly, the provision of up-to-date, open source DFO algorithms allows benchmarking in the future development of free, fast, accurate, and robust approaches for ASD. Thirdly, the ODAS approach can be directly used to develop building and city information models for various value-added applications. Numéro de notice : A2019-070 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.12.005 date de publication en ligne : 18/12/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.12.005 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92157 [article]

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A symmetry detector for map generalization and urban-space analysis / Jan‐Henrik Haunert in ISPRS Journal of photogrammetry and remote sensing, vol 74 (Novembrer 2012)

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 74 (Novembrer 2012) . - pp 66 - 77 Titre : A symmetry detector for map generalization and urban-space analysis Type de document : Article/Communication Auteurs : Jan‐Henrik Haunert, Auteur Année de publication : 2012 Article en page(s) : pp 66 - 77 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] agrégation de détails [Termes descripteurs IGN] analyse spatiale [Termes descripteurs IGN] bati [Termes descripteurs IGN] Boston (Massachusetts) [Termes descripteurs IGN] données vectorielles [Termes descripteurs IGN] empreinte [Termes descripteurs IGN] généralisation cartographique automatisée [Termes descripteurs IGN] indice de symétrie [Termes descripteurs IGN] polygone [Termes descripteurs IGN] simplification de contour [Vedettes matières IGN] Généralisation Résumé : (Auteur) This article presents an algorithmic approach to the problem of finding symmetries in building footprints, which is motivated by map generalization tasks such as symmetry-preserving building simplification and symmetry-aware grouping and aggregation. Moreover, symmetries in building footprints may be used for landmark selection and building classification. The presented method builds up on existing methods for symmetry detection in vector data that use algorithms for string matching. It detects both mirror symmetries and repetitions of geometric structures. In addition to the existing vector-based methods, the new method finds partial symmetries in polygons while allowing for small geometric errors and, based on a least-squares approach, computes optimally adjusted mirror axes and assesses their quality. Finally, the problem of grouping symmetry relations is addressed with an algorithm that finds mirror axes that are almost collinear. The presented approach was tested on a large building dataset of the metropolitan Boston area and its results were compared with results that were manually generated in an empirical test. The symmetry relations that the participants of the test considered most important were found by the algorithm. Future work will deal with the integration of information on symmetry relations into algorithms for map generalization. Numéro de notice : A2012-604 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32050 [article]

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