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A multi-scale plane-detection method based on the Hough transform and region growing / Xiaoxu Leng in Photogrammetric record, vol 31 n° 154 (June - August 2016)
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Titre : A multi-scale plane-detection method based on the Hough transform and region growing Type de document : Article/Communication Auteurs : Xiaoxu Leng, Auteur ; Jun Xiao, Auteur ; Ying Wang, Auteur Année de publication : 2016 Article en page(s) : pp 166 - 192 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] détection automatique
[Termes IGN] modélisation 3D
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] traitement d'image
[Termes IGN] transformation de HoughRésumé : (auteur) The detection of planes from 3D point clouds plays an important role in fields such as 3D modelling, rock mechanics, registration and robotics. A multi-scale plane-detection method is proposed, based on extracting growth units using the Hough transform and subsequent region growing into actual plane boundaries. Because the approximate geometric features of the original plane area can be obtained from the growth units, discriminant conditions for adaptive plane growing could be provided for the growing stage. In order to detect physical planes at different scales, a strategy of multi-scale normal estimation is introduced. Simulated icosahedron point clouds, together with actual engineering point clouds, were used to test the performance of the proposed method. Experimental results show that planar point clouds could be detected effectively, especially with rock-mass engineering applications. Numéro de notice : A2016-467 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12145 Date de publication en ligne : 17/06/2016 En ligne : https://doi.org/10.1111/phor.12145 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81473
in Photogrammetric record > vol 31 n° 154 (June - August 2016) . - pp 166 - 192[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 106-2016021 RAB Revue Centre de documentation En réserve L003 Disponible Privacy and spatial pattern preservation in masked GPS trajectory data / Dara E. Seidl in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)
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Titre : Privacy and spatial pattern preservation in masked GPS trajectory data Type de document : Article/Communication Auteurs : Dara E. Seidl, Auteur ; Piotr Jankowski, Auteur ; Ming-Hsiang Tsou, Auteur Année de publication : 2016 Article en page(s) : pp 785 - 800 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Atlanta (Géorgie)
[Termes IGN] Chicago (Illinois)
[Termes IGN] itinéraire
[Termes IGN] protection de la vie privée
[Termes IGN] régression linéaire
[Termes IGN] seuillage
[Termes IGN] traitement de données localisées
[Termes IGN] trajectographie par GNSSRésumé : (Auteur) Personal trajectory data are increasingly collected for a variety of academic and recreational pursuits. As access to location data widens and locations are linked to other information repositories, individuals become increasingly vulnerable to identification. The quality and precision of spatially linked attributes are essential to accurate analysis; yet, there is a trade-off between privacy and geographic data resolution. Obfuscation of point data, or masking, is a solution that aims to protect privacy and maximize preservation of spatial pattern. Trajectory data, with multiple locations recorded for an entity over time, is a strong personal identifier. This study explores the balance between privacy and spatial pattern resulting from two methods of obfuscation for personal GPS data: grid masking and random perturbation. These methods are applied to travel survey GPS data in the greater metropolitan regions of Chicago and Atlanta. The rate of pattern correlation between the original and masked data sets declines as the distance thresholds for masking increase. Grid masking at the 250-m threshold preserves route anonymity better than other methods and distance thresholds tested, but preserves spatial pattern least. This study also finds via linear regression that median trip speed and road density are significant predictors of trip anonymity. Numéro de notice : A2016-097 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1101767 En ligne : https://doi.org/10.1080/13658816.2015.1101767 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79894
in International journal of geographical information science IJGIS > vol 30 n° 3-4 (March - April 2016) . - pp 785 - 800[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016021 RAB Revue Centre de documentation En réserve L003 Disponible Spatial optimization for regionalization problems with spatial interaction: a heuristic approach / Kamyoung Kim in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)
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Titre : Spatial optimization for regionalization problems with spatial interaction: a heuristic approach Type de document : Article/Communication Auteurs : Kamyoung Kim, Auteur ; Denis J. Dean, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 451 - 473 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] interaction spatiale
[Termes IGN] méthode heuristique
[Termes IGN] optimisation spatiale
[Termes IGN] régionalisation (segmentation)Résumé : (Auteur) Spatial optimization techniques are commonly used for regionalization problems, often represented as p-regions problems. Although various spatial optimization approaches have been proposed for finding exact solutions to p-regions problems, these approaches are not practical when applied to large-size problems. Alternatively, various heuristics provide effective ways to find near-optimal solutions for p-regions problem. However, most heuristic approaches are specifically designed for particular geographic settings. This paper proposes a new heuristic approach named Automated Zoning Procedure-Center Interchange (AZP-CI) to solve the p-functional regions problem (PFRP), which constructs regions by combining small areas that share common characteristics with predefined functional centers and have tight connections among themselves through spatial interaction. The AZP-CI consists of two subprocesses. First, the dissolving/splitting process enhances diversification and thereby produces an extensive exploration of the solution space. Second, the standard AZP locally improves the objective value. The AZP-CI was tested using randomly simulated datasets and two empirical datasets with different sizes. These evaluations indicate that AZP-CI outperforms two established heuristic algorithms: the AZP and simulated annealing, in terms of both solution quality and consistency of producing reliable solutions regardless of initial conditions. It is also noted that AZP-CI, as a general heuristic method, can be easily extended to other regionalization problems. Furthermore, the AZP-CI could be a more scalable algorithm to solve computational intensive spatial optimization problems when it is combined with cyberinfrastructure. Numéro de notice : A2016-203 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1031671 En ligne : https://doi.org/10.1080/13658816.2015.1031671 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79889
in International journal of geographical information science IJGIS > vol 30 n° 3-4 (March - April 2016) . - pp 451 - 473[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016021 RAB Revue Centre de documentation En réserve L003 Disponible Object classification and recognition from mobile laser scanning point clouds in a road environment / Matti Lehtomäki in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)
[article]
Titre : Object classification and recognition from mobile laser scanning point clouds in a road environment Type de document : Article/Communication Auteurs : Matti Lehtomäki, Auteur ; Anttoni Jaakkola, Auteur ; Juha Hyyppä, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 1226 - 1239 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage automatique
[Termes IGN] classification automatique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] histogramme
[Termes IGN] reconnaissance d'objets
[Termes IGN] réseau routier
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] télémétrie laser mobile
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) Automatic methods are needed to efficiently process the large point clouds collected using a mobile laser scanning (MLS) system for surveying applications. Machine-learning-based object recognition from MLS point clouds in a road and street environment was studied in order to create maps from the road environment infrastructure. The developed automatic processing workflow included the following phases: the removal of the ground and buildings, segmentation, segment classification, and object location estimation. Several novel geometry-based features, which were previously applied in autonomous driving and general point cloud processing, were applied for the segment classification of MLS point clouds. The features were divided into three sets, i.e., local descriptor histograms (LDHs), spin images, and general shape and point distribution features, respectively. These were used in the classification of the following roadside objects: trees, lamp posts, traffic signs, cars, pedestrians, and hoardings. The accuracy of the object recognition workflow was evaluated using a data set that contained more than 400 objects. LDHs and spin images were applied for the first time for machine-learning-based object classification in MLS point clouds in the surveying applications of the road and street environment. The use of these features improved the classification accuracy by 9.6% (resulting in 87.9% accuracy) compared with the accuracy obtained using 17 general shape and point distribution features that represent the current state of the art in the field of MLS; therefore, significant improvement in the classification accuracy was achieved. Connected component segmentation and ground extraction were the cause of most of the errors and should be thus improved in the future. Numéro de notice : A2016-120 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2476502 En ligne : https://doi.org/10.1109/TGRS.2015.2476502 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80000
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 2 (February 2016) . - pp 1226 - 1239[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2016021 SL Revue Centre de documentation Revues en salle Disponible
Titre : 3D watertight mesh generation with uncertainties from ubiquitous data Type de document : Article/Communication Auteurs : Laurent Caraffa , Auteur ; Mathieu Brédif , Auteur ; Bruno Vallet , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2016 Collection : Lecture notes in Computer Science, ISSN 0302-9743 num. 10114 Projets : IQmulus / Métral, Claudine Conférence : ACCV 2016, 13th Asian Conference on Computer Vision 20/11/2016 24/11/2016 Taipei Taiwan Proceedings Springer Importance : pp 377 - 391 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme Graph-Cut
[Termes IGN] carte de confiance
[Termes IGN] distance de Hausdorff
[Termes IGN] incertitude géométrique
[Termes IGN] maille triangulaire
[Termes IGN] reconstruction d'objet
[Termes IGN] semis de points
[Termes IGN] seuillage
[Termes IGN] surface imperméable
[Termes IGN] théorie de Dempster-ShaferRésumé : (auteur) In this paper, we propose a generic framework for watertight mesh generation with uncertainties that provides a confidence measure on each reconstructed mesh triangle. Its input is a set of vision-based or Lidar-based 3D measurements which are converted to a set of mass functions that characterize the level of confidence on the occupancy of the scene as occupied, empty or unknown based on Dempster-Shafer Theory. The output is a multi-label segmentation of the ambient 3D space expressing the confidence for each resulting volume element to be occupied or empty. While existing methods either sacrifice watertightness (local methods) or need to introduce a smoothness prior (global methods), we derive a per-triangle confidence measure that is able to gradually characterize when the resulting surface patches are certain due to dense and coherent measurements and when these patches are more uncertain and are mainly present to ensure smoothness and/or watertightness. The surface mesh reconstruction is formulated as a global energy minimization problem efficiently optimized with the α-expansion algorithm. We claim that the resulting confidence measure is a good estimate of the local lack of sufficiently dense and coherent input measurements, which would be a valuable input for the next-best-view scheduling of a complementary acquisition.
Beside the new formulation, the proposed approach achieves state-of-the-art results on surface reconstruction benchmark. It is robust to noise, manages high scale disparity and produces a watertight surface with a small Hausdorff distance in uncertainty area thanks to the multi-label formulation. By simply thresholding the result, the method shows a good reconstruction quality compared to local algorithms on high density data. This is demonstrated on a large scale reconstruction combining real-world datasets from airborne and terrestrial Lidar and on an indoor scene reconstructed from images.Numéro de notice : C2016-024 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-319-54190-7_23 Date de publication en ligne : 12/03/2017 En ligne : http://doi.org/10.1007/978-3-319-54190-7_23 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84627 Documents numériques
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