Descripteur
Termes IGN > informatique > traitement automatique de données
traitement automatique de donnéesSynonyme(s)traitement automatique de l'infomationVoir aussi |
Documents disponibles dans cette catégorie (215)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Filtering airborne LiDAR data by embedding smoothness-constrained segmentation in progressive TIN densification / Jixian Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 81 (July 2013)
[article]
Titre : Filtering airborne LiDAR data by embedding smoothness-constrained segmentation in progressive TIN densification Type de document : Article/Communication Auteurs : Jixian Zhang, Auteur ; Xiangguo Lin, Auteur Année de publication : 2013 Article en page(s) : pp 44 - 59 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] densification
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage du signal
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] traitement automatique de données
[Termes IGN] Triangulated Irregular NetworkRésumé : (Auteur) Progressive TIN densification (PTD) is one of the classic methods for filtering airborne LiDAR point clouds. However, it may fail to preserve ground measurements in areas with steep terrain. A method is proposed to improve the PTD using a point cloud segmentation method, namely segmentation using smoothness constraint (SUSC). The classic PTD has two core steps. The first is selecting seed points and constructing the initial TIN. The second is an iterative densification of the TIN. Our main improvement is embedding the SUSC between these two steps. Specifically, after selecting the lowest points in each grid cell as initial ground seed points, SUSC is employed to expand the set of ground seed points as many as possible, as this can identify more ground seed points for the subsequent densification of the TIN-based terrain model. Seven datasets of ISPRS Working Group III/3 are utilized to test our proposed algorithm and the classic PTD. Experimental results suggest that, compared with the PTD, the proposed method is capable of preserving discontinuities of landscapes and reducing the omission errors and total errors by approximately 10% and 6% respectively, which would significantly decrease the cost of the manual operation required for correcting the result in post-processing. Numéro de notice : A2013-388 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.04.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.04.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32526
in ISPRS Journal of photogrammetry and remote sensing > vol 81 (July 2013) . - pp 44 - 59[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2013071 RAB Revue Centre de documentation En réserve L003 Disponible A shape-based segmentation method for mobile laser scanning point clouds / Yang Bisheng in ISPRS Journal of photogrammetry and remote sensing, vol 81 (July 2013)
[article]
Titre : A shape-based segmentation method for mobile laser scanning point clouds Type de document : Article/Communication Auteurs : Yang Bisheng, Auteur ; Zhen Dong, Auteur Année de publication : 2013 Article en page(s) : pp 19 - 30 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] connexité (topologie)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] traitement automatique de donnéesRésumé : (Auteur) Segmentation of mobile laser point clouds of urban scenes into objects is an important step for post-processing (e.g., interpretation) of point clouds. Point clouds of urban scenes contain numerous objects with significant size variability, complex and incomplete structures, and holes or variable point densities, raising great challenges for the segmentation of mobile laser point clouds. This paper addresses these challenges by proposing a shape-based segmentation method. The proposed method first calculates the optimal neighborhood size of each point to derive the geometric features associated with it, and then classifies the point clouds according to geometric features using support vector machines (SVMs). Second, a set of rules are defined to segment the classified point clouds, and a similarity criterion for segments is proposed to overcome over-segmentation. Finally, the segmentation output is merged based on topological connectivity into a meaningful geometrical abstraction. The proposed method has been tested on point clouds of two urban scenes obtained by different mobile laser scanners. The results show that the proposed method segments large-scale mobile laser point clouds with good accuracy and computationally effective time cost, and that it segments pole-like objects particularly well. Numéro de notice : A2013-386 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.04.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.04.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32524
in ISPRS Journal of photogrammetry and remote sensing > vol 81 (July 2013) . - pp 19 - 30[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2013071 RAB Revue Centre de documentation En réserve L003 Disponible An object-based system for Lidar data fusion and feature extraction / Jarlath P. M. O'Neil-Dunne in Geocarto international, vol 28 n° 3-4 (June - July 2013)
[article]
Titre : An object-based system for Lidar data fusion and feature extraction Type de document : Article/Communication Auteurs : Jarlath P. M. O'Neil-Dunne, Auteur ; Sean W. Macfaden, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 227 - 242 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] carte d'occupation du sol
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] données vectorielles
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] fusion de données
[Termes IGN] image aérienne
[Termes IGN] milieu urbain
[Termes IGN] modèle orienté objet
[Termes IGN] occupation du sol
[Termes IGN] Philadelphie
[Termes IGN] villeRésumé : (Auteur) In urbanized areas of the developed world, light detection and ranging (LiDAR) exists alongside a wealth of other geospatial information. Despite this bounty, high-resolution land cover is still lacking in many urban areas. This can be attributed to the complexity of many landscapes, the volume of available data and the challenges associated with combining data that were acquired over differing time periods using inconsistent standards. Object-based approaches are ideal for overcoming these limitations. We describe the design, development and deployment of an object-based system that incorporated LiDAR, imagery and vector data sets to develop a comprehensive, multibillion-pixel land-cover data set for the City of Philadelphia. A novel approach using parallel processing allowed us to distribute the feature extraction load to multiple cores, providing massive gains in efficiency and permitting continual modification of the expert system until the accuracy goals of the project were achieved. Numéro de notice : A2013-397 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.689015 Date de publication en ligne : 29/05/2012 En ligne : https://doi.org/10.1080/10106049.2012.689015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32535
in Geocarto international > vol 28 n° 3-4 (June - July 2013) . - pp 227 - 242[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2013021 RAB Revue Centre de documentation En réserve L003 Disponible Geometric calibration of a terrestrial laser scanner with local additional parameters: An automatic strategy / D. Garcia-San-Miguel in ISPRS Journal of photogrammetry and remote sensing, vol 79 (May 2013)
[article]
Titre : Geometric calibration of a terrestrial laser scanner with local additional parameters: An automatic strategy Type de document : Article/Communication Auteurs : D. Garcia-San-Miguel, Auteur ; J.L. Lerma, Auteur Année de publication : 2013 Article en page(s) : pp 122 - 136 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] erreur systématique
[Termes IGN] étalonnage géométrique
[Termes IGN] semis de points
[Termes IGN] télémètre laser terrestre
[Termes IGN] traitement automatique de donnéesRésumé : (Auteur) Terrestrial laser scanning systems are steadily increasing in many fields of engineering, geoscience and architecture namely for fast data acquisition, 3-D modeling and mapping. Similarly to other precision instruments, these systems provide measurements with implicit systematic errors. Systematic errors are physically corrected by manufacturers before delivery and sporadically afterwards. The approach presented herein tackles the raw observables acquired by a laser scanner with additional parameters, a set of geometric calibration parameters that model the systematic error of the instrument to achieve the most accurate point cloud outputs, improving eventual workflow owing to less filtering, better registration and best 3D modeling. This paper presents a fully automatic strategy to calibrate geometrically terrestrial laser scanning datasets. The strategy is tested with multiple scans taken by a FARO FOCUS 3D, a phase-based terrestrial laser scanner. A calibration with local parameters for datasets is undertaken to improve the raw observables and a weighted mathematical index is proposed to select the most significant set of additional parameters. The improvements achieved are exposed, highlighting the necessity of correcting the terrestrial laser scanner before handling multiple data sets. Numéro de notice : A2013-235 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.02.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.02.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32373
in ISPRS Journal of photogrammetry and remote sensing > vol 79 (May 2013) . - pp 122 - 136[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2013051 RAB Revue Centre de documentation En réserve L003 Disponible Towards 3D lidar point cloud registration improvement using optimal neighborhood knowledge / Adrien Gressin in ISPRS Journal of photogrammetry and remote sensing, vol 79 (May 2013)
[article]
Titre : Towards 3D lidar point cloud registration improvement using optimal neighborhood knowledge Type de document : Article/Communication Auteurs : Adrien Gressin , Auteur ; Clément Mallet , Auteur ; Jérôme Demantké , Auteur ; Nicolas David , Auteur Année de publication : 2013 Projets : 1-Pas de projet / Article en page(s) : pp 240 - 251 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme ICP
[Termes IGN] analyse diachronique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] semis de points
[Termes IGN] superposition de données
[Termes IGN] valeur propre
[Termes IGN] voisinage (relation topologique)Résumé : (Auteur) Automatic 3D point cloud registration is a main issue in computer vision and remote sensing. One of the most commonly adopted solution is the well-known Iterative Closest Point (ICP) algorithm. This standard approach performs a fine registration of two overlapping point clouds by iteratively estimating the transformation parameters, assuming good a priori alignment is provided. A large body of literature has proposed many variations in order to improve each step of the process (namely selecting, matching, rejecting, weighting and minimizing). The aim of this paper is to demonstrate how the knowledge of the shape that best fits the local geometry of each 3D point neighborhood can improve the speed and the accuracy of each of these steps. First, we present the geometrical features that form the basis of this work. These low-level attributes indeed describe the neighborhood shape around each 3D point. They allow to retrieve the optimal size to analyze the neighborhoods at various scales as well as the privileged local dimension (linear, planar, or volumetric). Several variations of each step of the ICP process are then proposed and analyzed by introducing these features. Such variants are compared on real datasets with the original algorithm in order to retrieve the most efficient algorithm for the whole process. Therefore, the method is successfully applied to various 3D lidar point clouds from airborne, terrestrial, and mobile mapping systems. Improvement for two ICP steps has been noted, and we conclude that our features may not be relevant for very dissimilar object samplings. Numéro de notice : A2013-240 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.02.019 Date de publication en ligne : 01/04/2013 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2013.02.019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32378
in ISPRS Journal of photogrammetry and remote sensing > vol 79 (May 2013) . - pp 240 - 251[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2013051 RAB Revue Centre de documentation En réserve L003 Disponible Mise en cohérence de données laser cartographique par recalage non-rigide / Fabrice Monnier in Revue Française de Photogrammétrie et de Télédétection, n° 202 (Avril 2013)PermalinkObject-based fusion of multitemporal multiangle ENVISAT ASAR and HJ-1B multispectral data for urban land-cover mapping / Yifang Ban in IEEE Transactions on geoscience and remote sensing, vol 51 n° 4 Tome 1 (April 2013)PermalinkParallel indexing technique for spatio-temporal data / Zhenwen He in ISPRS Journal of photogrammetry and remote sensing, vol 78 (April 2013)PermalinkPedestrian network extraction from fused aerial imagery (orthoimages) and laser imagery (lidar) / Piyawan Kasemsuppakorn in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 4 (April 2013)PermalinkGeneration and dissemination of a national virtual 3D city and landscape model for the Netherlands / Sander J. Elberink in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 2 (February 2013)PermalinkA multi-scale approach to mapping canopy height / Gordon M. Green in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 2 (February 2013)PermalinkSegmentation of terrestrial laser scanning data using geometry and image information / S. Barnea in ISPRS Journal of photogrammetry and remote sensing, vol 76 (February 2013)PermalinkCalibration extrinsèque d'un scanner laser multi-fibre / Anthony Wiart (2013)PermalinkPermalinkA multi-granularity parallel model for unified remote sensing image processing webservices / W. Guo in Transactions in GIS, vol 16 n° 6 (December 2012)Permalink