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Pairwise coarse registration of point clouds in urban scenes using voxel-based 4-planes congruent sets / Yusheng Xu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 106 - 123 Titre : Pairwise coarse registration of point clouds in urban scenes using voxel-based 4-planes congruent sets Type de document : Article/Communication Auteurs : Yusheng Xu, Auteur ; Richard Boerner, Auteur ; Wei Yao, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 106 - 123 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] congruence [Termes descripteurs IGN] données 4D [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] modèle stéréoscopique [Termes descripteurs IGN] octree [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] scène urbaine [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] surface plane [Termes descripteurs IGN] voxel Résumé : (Auteur) To ensure complete coverage when measuring a large-scale urban area, pairwise registration between point clouds acquired via terrestrial laser scanning or stereo image matching is usually necessary when there is insufficient georeferencing information from additional GNSS and INS sensors. In this paper, we propose a semi-automatic and target-less method for coarse registration of point clouds using geometric constraints of voxel-based 4-plane congruent sets (V4PCS). The planar patches are firstly extracted from voxelized point clouds. Then, the transformation invariant, 4-plane congruent sets are constructed from extracted planar surfaces in each point cloud. Initial transformation parameters between point clouds are estimated via corresponding congruent sets having the highest registration scores in the RANSAC process. Finally, a closed-form solution is performed to achieve optimized transformation parameters by finding all corresponding planar patches using the initial transformation parameters. Experimental results reveal that our proposed method can be effective for registering point clouds acquired from various scenes. A success rate of better than 80% was achieved, with average rotation errors of about 0.5 degrees and average translation errors less than approximately 0.6 m. In addition, our proposed method is more efficient than other baseline methods when using the same hardware and software configuration conditions. Numéro de notice : A2019-207 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.02.015 date de publication en ligne : 18/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.02.015 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92673 [article]

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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 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 voxel- and graph-based strategy for segmenting man-made infrastructures using perceptual grouping laws: comparison and evaluation / Yusheng Xu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 6 (juin 2018)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 6 (juin 2018) . - pp 377 - 391 Titre : A voxel- and graph-based strategy for segmenting man-made infrastructures using perceptual grouping laws: comparison and evaluation Type de document : Article/Communication Auteurs : Yusheng Xu, Auteur ; Ludwig Hoegner, Auteur ; Sebastian Tuttas, Auteur ; Uwe Stilla, Auteur Année de publication : 2018 Article en page(s) : pp 377 - 391 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] bati [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] octree [Termes descripteurs IGN] partition des données [Termes descripteurs IGN] prise en compte du contexte [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] scène urbaine [Termes descripteurs IGN] segmentation [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] théorie des graphes [Termes descripteurs IGN] voxel Résumé : (auteur) In this paper, we report a novel strategy for segmenting 3D point clouds using a voxel structure and graph-based clustering with perceptual grouping laws. It provides a completely automatic solution for partitioning point clouds of man-made infrastructure. Two different segmentation methods using voxel and supervoxel structures are presented and evaluated. To increase the efficiency and the robustness of the segmentation process, the voxelization with octree-based structure is introduced, which can suppress effects of noise, outliers, and unevenly distributed point densities as well. The clustering of over-segmented voxels and supervoxels is achieved using graph theory on the basis of the local contextual information, which is commonly conducted merely with pairwise information in conventional clustering algorithms. The graphical model is constructed according to perceptual grouping laws, considering geometric information associated with points. Experiments using both laser scanning and photogrammetric point clouds have demonstrated that the proposed methods can achieve good results, especially complex scenes and nonplanar object surfaces, with F1-measures better than 0.67 for all the testing samples. Quantitative comparisons between the proposed approaches and other representative segmentation methods also confirm the effectiveness and the efficiency of the former. Moreover, a series of experiments is carried out, to investigate the methods' sensitivity with respect to various parameters on the segmentation results. Numéro de notice : A2018-231 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.6.377 date de publication en ligne : 01/06/2018 En ligne : https://doi.org/10.14358/PERS.84.6.377 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90173 [article]

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A spatio-temporal index for aerial full waveform laser scanning data / Debra F. Laefer in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 138 (April 2018) . - pp 232 - 251 Titre : A spatio-temporal index for aerial full waveform laser scanning data Type de document : Article/Communication Auteurs : Debra F. Laefer, Auteur ; Anh-Vu Vo, Auteur ; Michela Bertolotto, Auteur Année de publication : 2018 Article en page(s) : pp 232 - 251 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] Arbre-R [Termes descripteurs IGN] base de données localisées [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] forme d'onde pleine [Termes descripteurs IGN] index spatiotemporel [Termes descripteurs IGN] indexation spatiale [Termes descripteurs IGN] octree Résumé : (Auteur) Aerial laser scanning is increasingly available in the full waveform version of the raw signal, which can provide greater insight into and control over the data and, thus, richer information about the scanned scenes. However, when compared to conventional discrete point storage, preserving raw waveforms leads to vastly larger and more complex data volumes. To begin addressing these challenges, this paper introduces a novel bi-level approach for storing and indexing full waveform (FWF) laser scanning data in a relational database environment, while considering both the spatial and the temporal dimensions of that data. In the storage scheme's upper level, the full waveform datasets are partitioned into spatial and temporal coherent groups that are indexed by a two-dimensional R∗-tree. To further accelerate intra-block data retrieval, at the lower level a three-dimensional local octree is created for each pulse block. The local octrees are implemented in-memory and can be efficiently written to a database for reuse. The indexing solution enables scalable and efficient three-dimensional (3D) spatial and spatio-temporal queries on the actual pulse data - functionalities not available in other systems. The proposed FWF laser scanning data solution is capable of managing multiple FWF datasets derived from large flight missions. The flight structure is embedded into the data storage model and can be used for querying predicates. Such functionality is important to FWF data exploration since aircraft locations and orientations are frequently required for FWF data analyses. Empirical tests on real datasets of up to 1 billion pulses from Dublin, Ireland prove the almost perfect scalability of the system. The use of the local 3D octree in the indexing structure accelerated pulse clipping by 1.2–3.5 times for non-axis-aligned (NAA) polyhedron shaped clipping windows, while axis-aligned (AA) polyhedron clipping was better served using only the top indexing layer. The distinct behaviours of the hybrid indexing for AA and NAA clipping windows are attributable to the different proportion of the local-index-related overheads with respect to the total querying costs. When temporal constraints were added, generally the number of costly spatial checks were reduced, thereby shortening the querying times. Numéro de notice : A2018-125 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89587 [article]

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Semantic enrichment of octree structured point clouds for multi‐story 3D pathfinding / Florian W. Fichtner in Transactions in GIS, vol 22 n° 1 (February 2018)  

Public [article]  inTransactions in GIS > vol 22 n° 1 (February 2018) . - pp 233 - 248 Titre : Semantic enrichment of octree structured point clouds for multi‐story 3D pathfinding Type de document : Article/Communication Auteurs : Florian W. Fichtner, Auteur ; Abdoulaye A. Diakité, Auteur ; Sisi Zlatanova, Auteur ; Robert Voûte, Auteur Année de publication : 2018 Article en page(s) : pp 233 - 248 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] calcul d'itinéraire [Termes descripteurs IGN] espace intérieur vide [Termes descripteurs IGN] information sémantique [Termes descripteurs IGN] octree [Termes descripteurs IGN] positionnement en intérieur [Termes descripteurs IGN] semis de points Résumé : (auteur) 3D indoor navigation in multi‐story buildings and under changing environments is still difficult to perform. 3D models of buildings are commonly not available or outdated. 3D point clouds turned out to be a very practical way to capture 3D interior spaces and provide a notion of an empty space. Therefore, pathfinding in point clouds is rapidly emerging. However, processing of raw point clouds can be very expensive, as these are semantically poor and unstructured data. In this article we present an innovative octree‐based approach for processing of 3D indoor point clouds for the purpose of multi‐story pathfinding. We semantically identify the construction elements, which are of importance for the indoor navigation of humans (i.e., floors, walls, stairs, and obstacles), and use these to delineate the available navigable space. To illustrate the usability of this approach, we applied it to real‐world data sets and computed paths considering user constraints. The structuring of the point cloud into an octree approximation improves the point cloud processing and provides a structure for the empty space of the point cloud. It is also helpful to compute paths sufficiently accurate in their consideration of the spatial complexity. The entire process is automatic and able to deal with a large number of multi‐story indoor environments. Numéro de notice : A2018-067 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12308 En ligne : https://doi.org/10.1111/tgis.12308 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89423 [article]

Global, dense multiscale reconstruction for a billion points / Benjamin Ummenhofer in International journal of computer vision, vol 125 n° 1-3 (December 2017)  

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Etude et méthodes d'intégration et d'interaction de données 3D complexes type "nuages de points" vers un web SIG / Victor Lambert (2017) 

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Project pointless : pathfinding through identified empty space in point clouds / Tom Broersen in GIM international [en ligne], vol 30 n° 4 (April 2016)

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Octree-based segmentation for terrestrial LiDAR point cloud data in industrial applications / Yun-Ting Su in ISPRS Journal of photogrammetry and remote sensing, vol 113 (March 2016)  

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3D octree based watertight mesh generation from ubiquitous data / Laurent Caraffa (2015)  

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One billion points in the cloud – an octree for efficient processing of 3D laser scans / Jan Elseberg in ISPRS Journal of photogrammetry and remote sensing, vol 76 (February 2013)

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An efficient point cloud management method based on a 3D R-tree / J. Gong in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 4 (April 2012)

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Incremental segmentation of lidar point clouds with an octree-structured voxel space / M. Wang in Photogrammetric record, vol 26 n° 133 (March - May 2011)

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Automatic segmentation of Lidar data into coplanar point clusters using an octree-based split-and-merge algorithm / M. Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 4 (April 2010)

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