Descripteur
Termes IGN > mathématiques > statistique mathématique > analyse de données > Ransac (algorithme)
Ransac (algorithme)Synonyme(s)RANdom SAmple ConsensusVoir aussi |
Documents disponibles dans cette catégorie (46)
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
An improved RANSAC algorithm for extracting roof planes from airborne lidar data / Sibel Canaz Sevgen in Photogrammetric record, vol 35 n° 169 (March 2020)
[article]
Titre : An improved RANSAC algorithm for extracting roof planes from airborne lidar data Type de document : Article/Communication Auteurs : Sibel Canaz Sevgen, Auteur ; Fevzi Karsli, Auteur Année de publication : 2020 Article en page(s) : pp 40 - 57 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Algorithmique
[Termes IGN] bord décollé (toit)
[Termes IGN] contrôle qualité
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Ransac (algorithme)
[Termes IGN] segmentation en régions
[Termes IGN] semis de pointsRésumé : (Auteur) The extraction of building roof planes from lidar data has become a popular research topic with random sample consensus (RANSAC) being one of the most commonly adopted algorithms. RANSAC extracts full planes, which is problematic when there are other points outside the plane boundary but within the plane space. This study proposes an improved RANSAC (I‐RANSAC) algorithm by removing points that do not belong to the roof plane. I‐RANSAC selects a random point from the extracted roof plane and then searches for its neighbours within a given threshold to identify and remove outliers. The new algorithm was tested with 14 buildings from two datasets, where quality control measures showed significant improvement over standard RANSAC. Numéro de notice : A2020-131 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Numéro de périodique nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12296 Date de publication en ligne : 13/11/2019 En ligne : https://doi.org/10.1111/phor.12296 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94815
in Photogrammetric record > vol 35 n° 169 (March 2020) . - pp 40 - 57[article]Reducing shadow effects on the co-registration of aerial image pairs / Matthew Plummer in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 3 (March 2020)
[article]
Titre : Reducing shadow effects on the co-registration of aerial image pairs Type de document : Article/Communication Auteurs : Matthew Plummer, Auteur ; Douglas A. Stow, Auteur ; Emmanuel Storey, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 177 - 186 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de données
[Termes IGN] correction des ombres
[Termes IGN] détection automatique
[Termes IGN] détection de changement
[Termes IGN] effet d'ombre
[Termes IGN] enregistrement de données
[Termes IGN] image à haute résolution
[Termes IGN] image aérienne
[Termes IGN] image multitemporelle
[Termes IGN] intensité lumineuse
[Termes IGN] masque
[Termes IGN] Ransac (algorithme)
[Termes IGN] SIFT (algorithme)Résumé : (auteur) Image registration is an important preprocessing step prior to detecting changes using multi-temporal image data, which is increasingly accomplished using automated methods. In high spatial resolution imagery, shadows represent a major source of illumination variation, which can reduce the performance of automated registration routines. This study evaluates the statistical relationship between shadow presence and image registration accuracy, and whether masking and normalizing shadows leads to improved automatic registration results. Eighty-eight bitemporal aerial image pairs were co-registered using software called Scale Invariant Features Transform (SIFT) and Random Sample Consensus (RANSAC) Alignment (SARA). Co-registration accuracy was assessed at different levels of shadow coverage and shadow movement within the images. The primary outcomes of this study are (1) the amount of shadow in a multi-temporal image pair is correlated with the accuracy/success of automatic co-registration; (2) masking out shadows prior to match point select does not improve the success of image-to-image co-registration; and (3) normalizing or brightening shadows can help match point routines find more match points and therefore improve performance of automatic co-registration. Normalizing shadows via a standard linear correction provided the most reliable co-registration results in image pairs containing substantial amounts of relative shadow movement, but had minimal effect for pairs with stationary shadows. Numéro de notice : A2020-147 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.4.177 Date de publication en ligne : 01/03/2020 En ligne : https://doi.org/10.14358/PERS.86.4.177 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94776
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 3 (March 2020) . - pp 177 - 186[article]Automatic scale estimation of structure from motion based 3D models using laser scalers in underwater scenarios / Klemen Istenič in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)
[article]
Titre : Automatic scale estimation of structure from motion based 3D models using laser scalers in underwater scenarios Type de document : Article/Communication Auteurs : Klemen Istenič, Auteur ; Nuno Gracias, Auteur ; Aurélien Arnaubec, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 13 - 25 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] estimation de pose
[Termes IGN] étalonnage
[Termes IGN] faisceau laser
[Termes IGN] image à haute résolution
[Termes IGN] image sous-marine
[Termes IGN] photogrammétrie sous-marine
[Termes IGN] Ransac (algorithme)
[Termes IGN] reconstruction 3D
[Termes IGN] structure-from-motionRésumé : (Auteur) Improvements in structure-from-motion techniques are enabling many scientific fields to benefit from the routine creation of detailed 3D models. However, for a large number of applications, only a single camera is available for the image acquisition, due to cost or space constraints in the survey platforms. Monocular structure-from-motion raises the issue of properly estimating the scale of the 3D models, in order to later use those models for metrology. The scale can be determined from the presence of visible objects of known dimensions, or from information on the magnitude of the camera motion provided by other sensors, such as GPS. This paper addresses the problem of accurately scaling 3D models created from monocular cameras in GPS-denied environments, such as in underwater applications. Motivated by the common availability of underwater laser scalers, we present two novel approaches which are suitable for different laser scaler configurations. A fully unconstrained method enables the use of arbitrary laser setups, while a partially constrained method reduces the need for calibration by only assuming parallelism on the laser beams and equidistance with the camera. The proposed methods have several advantages with respect to existing methods. By using the known geometry of the scene represented by the 3D model, along with some parameters of the laser scaler geometry, the need for laser alignment with the optical axis of the camera is eliminated. Furthermore, the extremely error-prone manual identification of image points on the 3D model, currently required in image-scaling methods, is dispensed with. The performance of the methods and their applicability was evaluated both on data generated from a realistic 3D model and on data collected during an oceanographic cruise in 2017. Three separate laser configurations have been tested, encompassing nearly all possible laser setups, to evaluate the effects of terrain roughness, noise, camera perspective angle and camera-scene distance on the final estimates of scale. In the real scenario, the computation of 6 independent model scale estimates using our fully unconstrained approach, produced values with a standard deviation of 0,3 %. By comparing the values to the only other possible method currently usable for this dataset, we showed that the consistency of scales obtained for individual lasers is much higher for our approach (0,6 % compared to 4 %). Numéro de notice : A2020-010 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.10.007 Date de publication en ligne : 14/11/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.10.007 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94397
in ISPRS Journal of photogrammetry and remote sensing > vol 159 (January 2020) . - pp 13 - 25[article]Réservation
Réserver ce documentExemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020011 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020013 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020012 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Image processing applications in object detection and graph matching: from Matlab development to GPU framework / Beibei Cui (2020)
Titre : Image processing applications in object detection and graph matching: from Matlab development to GPU framework Type de document : Thèse/HDR Auteurs : Beibei Cui, Auteur ; Jean-Charles Créput, Directeur de thèse Editeur : Dijon : Université Bourgogne Franche-Comté UBFC Année de publication : 2020 Importance : 137 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse de Doctorat de l'Université Bourgogne Franche-Comté préparée à l'Université de Technologie de Belfort-Montbéliard, InformatiqueLangues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement de graphes
[Termes IGN] détection d'objet
[Termes IGN] entropie
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] graphe planaire
[Termes IGN] Matlab
[Termes IGN] ondelette
[Termes IGN] processeur graphique
[Termes IGN] Ransac (algorithme)
[Termes IGN] reconnaissance de formesIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Automatically finding correspondences between object features in images is of main interest for several applications, as object detection and tracking, flow velocity estimation, identification, registration, and many derived tasks. In this thesis, we address feature correspondence within the general framework of graph matching optimization and with the principal aim to contribute, at a final step, to the design of new and parallel algorithms and their implementation on GPU (Graphics Processing Unit) systems. Graph matching problems can have many declinations, depending on the assumptions of the application at hand. We observed a gap between applications based on local cost objective functions, and those applications with higher-order cost functions, that evaluate similarity between edges of the graphs, or hyperedges when considering hypergraphs. The former class provides convolution-based algorithms already having parallel GPU implementations. Whereas, the latter class puts the emphasis on geometric inter-feature relationships, transforming the correspondence problem to a purely geometric problem stated in a high dimensional space, generally modeled as an integer quadratic programming, for which we did not find GPU implementations available yet.Two complementary approaches were adopted in order to contribute to addressing higher-order geometric graph matching on GPU. Firstly, we study different declinations of feature correspondence problems by the use of the Matlab platform, in order to reuse and provide state-of-the-art solution methods, as well as experimental protocols and input data necessary for a GPU platform with evaluation and comparison tools against existing sequential algorithms, most of the time developed in Matlab framework. Then, the first part of this work concerns three contributions, respectively, to background and frame difference application, to feature extraction problem from images for local correspondences, and to the general graph matching problem, all based on the combination of methods derived from Matlab environment. Secondly, and based on the results of Matlab developments, we propose a new GPU framework written in CUDA C++ specifically dedicated to geometric graph matching but providing new parallel algorithms, with lower computational complexity, as the self-organizing map in the plane, derived parallel clustering algorithms, and distributed local search method. These parallel algorithms are then evaluated and compared to the state-of-the-art methods available for graph matching and following the same experimental protocol. This GPU platform constitutes our final and main proposal to contribute to bridging the gap between GPU development and higher-order graph matching. Note de contenu : 1- Introduction
2- Background
3- Background subtraction and frame difference for multi-object detection
4- Using Marr-wavelets and entropy/response to automatic feature detection
5- Affinity-preserving fixed point APRIP in Matlab framework for graph matching
6- Planar graph matching in GPU
7- Conclusion and future workNuméro de notice : 28328 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Informatique : UBFC : 2020 Organisme de stage : CIAD Dijon DOI : sans En ligne : https://tel.archives-ouvertes.fr/tel-02902973/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98402 Piecewise-planar approximation of large 3D data as graph-structured optimization / Stéphane Guinard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-2/W5 (May 2019)
[article]
Titre : Piecewise-planar approximation of large 3D data as graph-structured optimization Type de document : Article/Communication Auteurs : Stéphane Guinard , Auteur ; Loïc Landrieu , Auteur ; Laurent Caraffa , Auteur ; Bruno Vallet , Auteur Année de publication : 2019 Projets : 1-Pas de projet / Conférence : ISPRS 2019, Geospatial Week 10/06/2019 14/06/2019 Enschede Pays-Bas ISPRS OA Annals Article en page(s) : pp 365 - 372 Note générale : bibliographie
The authors would like to acknowledge the DGA for their financial support of this work.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme de décalage moyen
[Termes IGN] analyse de groupement
[Termes IGN] approximation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] érosion anthropique
[Termes IGN] erreur d'approximation
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] graphe
[Termes IGN] maillage
[Termes IGN] Ransac (algorithme)
[Termes IGN] semis de points
[Termes IGN] surface planeRésumé : (auteur) We introduce a new method for the piecewise-planar approximation of 3D data, including point clouds and meshes. Our method is designed to operate on large datasets (e.g. millions of vertices) containing planar structures, which are very frequent in anthropic scenes. Our approach is also adaptive to the local geometric complexity of the input data. Our main contribution is the formulation of the piecewise-planar approximation problem as a non-convex optimization problem. In turn, this problem can be efficiently solved with a graph-structured working set approach. We compare our results with a state-of-the-art region-growing-based segmentation method and show a significant improvement both in terms of approximation error and computation efficiency. Numéro de notice : A2019-592 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-IV-2-W5-365-2019 Date de publication en ligne : 29/05/2019 En ligne : https://doi.org/10.5194/isprs-annals-IV-2-W5-365-2019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94552
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol IV-2/W5 (May 2019) . - pp 365 - 372[article]Detecting and characterizing downed dead wood using terrestrial laser scanning / Tuomas Yrttimaa in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)PermalinkFusion of thermal imagery with point clouds for building façade thermal attribute mapping / Dong Lin in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)PermalinkPairwise 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)PermalinkMeasuring stem diameters with TLS in boreal forests by complementary fitting procedure / Timo P Pitkänen in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)PermalinkStructure from motion for ordered and unordered image sets based on random k-d forests and global pose estimation / Xin Wang in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)PermalinkExtraction of building roof planes with stratified random sample consensus / André C. Carrilho in Photogrammetric record, vol 33 n° 163 (September 2018)PermalinkThree-point-based solution for automated motion parameter estimation of a multi-camera indoor mapping system with planar motion constraint / Fangning He in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkMachine learning and pose estimation for autonomous robot grasping with collaborative robots / Victor Talbot (2018)PermalinkAlgebraic method to speed up robust algorithms: example of laser-scanned point clouds / B. Palancz in Survey review, vol 49 n° 357 (December 2017)PermalinkA Geometric and Radiometric Simultaneous Correction Model (GRSCM) framework for high-accuracy remotely sensed image preprocessing / Chang Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 9 (September 2017)PermalinkMise en place d’un processus de dessin automatisé de plans d’intérieurs à partir de nuages de points acquis par LIDAR / Léa Talec (2017)PermalinkAutomatic registration of MLS point clouds and SfM meshes of urban area / Reiji Yoshimura in Geo-spatial Information Science, vol 19 n° 3 (October 2016)PermalinkThe reliability of RANSAC method when estimating the parameters of geometric object / Tilen Urbančič in Geodetski vestnik, vol 60 n° 1 (March - May 2016)PermalinkPermalinkConception d’une méthode de consolidation de grands réseaux lasergrammétriques / Emmanuel Clédat (2015)PermalinkAssociation-matrix-based sample consensus approach for automated registration of terrestrial laser scans using linear features / Kaleel Al-Durgham in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 11 (November 2014)PermalinkA robust image matching method based on optimized BaySAC / Zhizhong Kang in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 11 (November 2014)PermalinkAutomatic registration of coastal remotely sensed imagery by affine invariant feature matching with shoreline constraint / Liang Cheng in Marine geodesy, vol 37 n° 1 (March - May 2014)PermalinkA new method for automatic large scale map updating using mobile mapping imagery / Jianliang Ou in Photogrammetric record, vol 28 n° 143 (September - November 2013)PermalinkRegistration of aerial imagery and lidar data in desert areas using the centroids of bushes as control information / Na Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 8 (August 2013)Permalink