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Termes descripteurs IGN > sciences naturelles > physique > traitement d'image > acquisition d'images > modélisation de prise de vue > modélisation géométrique de prise de vue > espace image
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Absolute orientation based on line coordinates / Qing H. Sheng in Photogrammetric record, vol 32 n° 157 (March - May 2017)
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[article]
Titre : Absolute orientation based on line coordinates Type de document : Article/Communication Auteurs : Qing H. Sheng, Auteur ; Bing Zhang, Auteur Année de publication : 2017 Article en page(s) : pp 12 - 32 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes descripteurs IGN] contour
[Termes descripteurs IGN] coordonnées géographiques
[Termes descripteurs IGN] espace image
[Termes descripteurs IGN] espace objet
[Termes descripteurs IGN] géoréférencement direct
[Termes descripteurs IGN] orientation absolue
[Termes descripteurs IGN] point d'appui
[Termes descripteurs IGN] segment de droite
[Termes descripteurs IGN] système de coordonnéesRésumé : (auteur) Absolute orientation based on points is a common method of precise georeferencing in photogrammetry. In images of urban areas, straight-line features such as buildings are prominent. A new absolute orientation approach dependent on line coordinates is proposed in this paper. An arbitrary spatial line can be described by its orientation vector and moment vector. Using the helical scaling displacement operator, the transformation of straight lines in model space and their corresponding control straight lines in object space can be achieved. Experimental results show that with eight control straight lines, the proposed approach is comparable to the precision of absolute orientation using four control points. Furthermore, the endpoints of corresponding line segments in the two spaces are not required to be conjugate points. Numéro de notice : A2017-195 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article En ligne : http://dx.doi.org/10.1111/phor.12178 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84869
in Photogrammetric record > vol 32 n° 157 (March - May 2017) . - pp 12 - 32[article]Automatic modeling of building interiors using low-cost sensor systems / Ali Mohammad Khosravani (2016)
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Titre : Automatic modeling of building interiors using low-cost sensor systems Type de document : Thèse/HDR Auteurs : Ali Mohammad Khosravani, Auteur ; Dieter Fritsch, Directeur de thèse Editeur : Munich : Bayerische Akademie der Wissenschaften Année de publication : 2016 Collection : DGK - C, ISSN 0065-5325 num. 767 Importance : 134 p. ISBN/ISSN/EAN : 978-3-7696-5179-9 Note générale : bibliographie
PhD DissertationLangues : Anglais (eng) Allemand (ger) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes descripteurs IGN] carte d'intérieur
[Termes descripteurs IGN] chambre de prise de vue numérique
[Termes descripteurs IGN] espace image
[Termes descripteurs IGN] espace objet
[Termes descripteurs IGN] Kinect
[Termes descripteurs IGN] modélisation 3D du bâti BIMRésumé : (auteur) Indoor reconstruction or 3D modeling of indoor scenes aims at representing the 3D shape of building interiors in terms of surfaces and volumes, using photographs, 3D point clouds or hypotheses. Due to advances in the range measurement sensors technology and vision algorithms, and at the same time an increased demand for indoor models by many applications, this topic of research has gained growing attention during the last years. The automation of the reconstruction process is still a challenge, due to the complexity of the data collection in indoor scenes, as well as geometrical modeling of arbitrary room shapes, especially if the data is noisy or incomplete. Available reconstruction approaches rely on either some level of user interaction, or making assumptions regarding the scene, in order to deal with the challenges. The presented work aims at increasing the automation level of the reconstruction task, while making fewer assumptions regarding the room shapes, even from the data collected by low-cost sensor systems subject to a high level of noise or occlusions. This is realized by employing topological corrections that assure a consistent and robust reconstruction. This study presents an automatic workflow consisting of two main phases. In the first phase, range data is collected using the affordable and accessible sensor system, Microsoft Kinect. The range data is registered based on features observed in the image space or 3D object space. A new complementary approach is presented to support the registration task in some cases where these registration approaches fail, due to the existence of insufficient visual and geometrical features. The approach is based on the user’s track information derived from an indoor positioning method, as well as an available coarse floor plan. In the second phase, 3D models are derived with a high level of details from the registered point clouds. The data is processed in 2D space (by projecting the points onto the ground plane), and the results are converted back to 3D by an extrusion (room height available from the point height histogram analysis). Data processing and modeling in 2D does not only simplify the reconstruction problem, but also allows for topological analysis using the graph theory. The performance of the presented reconstruction approach is demonstrated for the data derived from different sensors having different accuracies, as well as different room shapes and sizes. Finally, the study shows that the reconstructed models can be used to refine available coarse indoor models which are for instance derived from architectural drawings or floor plans. The refinement is performed by the fusion of the detailed models of individual rooms (reconstructed in a higher level of details by the new approach) to the coarse model. The model fusion also enables the reconstruction of gaps in the detailed model using a new learning-based approach. Moreover, the refinement process enables the detection of changes or details in the original plans, missing due to generalization purposes, or later renovations in the building interiors. Note de contenu : 1. Introduction
1.1. Motivation
1.2. Objectives
1.3. Outline and Design of the Thesis
2. Overview of Indoor Data Collection Techniques
2.1. State-of-the-Art Sensors for 3D Data Collection
2.2. The Registration Problem
3. Data Collection using Microsoft Kinect for Xbox 360
3.1. Point Cloud Collection by Kinect
3.2. Point Clouds Registration
3.3. Kinect SWOT Analysis
4. Overview of Available Indoor Modeling Approaches
4.1. Classification of Available Modeling Approaches
4.2. Iconic Approaches
4.3. Symbolic Approaches
5. Automatic Reconstruction of Indoor Spaces
5.1. Point Cloud Pre-Processing
5.2. Reconstruction of Geometric Models
6. Experimental Results and Analysis
6.1. Kinect System Calibration and Accuracy Analysis
6.2. Evaluation of the Reconstruction Approach
6.3. Quality of the Reconstructed Models
7. Application in the Refinement of Available Coarse Floor Models
7.1. Registration of Individual Detailed Models to an Available Coarse Floor Model
7.2. Fusion of Detailed Models to the Coarse Model
8. Conclusion
8.1. Summary
8.2. Contributions
8.3. Future WorkNuméro de notice : 19789 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD Dissertation : Photogrammetry : Stuttgart : 2016 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85007 Documents numériques
en open access
Automatic Modeling of Building Interiors Using Low-Cost Sensor SystemsAdobe Acrobat PDFRoad marking extraction using a model&data-driven RJ-MCMC / Alexandre Hervieu in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, II-3 W4 (March 2015)
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Titre : Road marking extraction using a model&data-driven RJ-MCMC Type de document : Article/Communication Auteurs : Alexandre Hervieu , Auteur ; Bahman Soheilian
, Auteur ; Mathieu Brédif
, Auteur
Congrès : ISPRS 2015, PIA 2015 - HRIGI 2015 Joint ISPRS conference (25 - 27 mars 2015; Munich, Allemagne), Commanditaire Année de publication : 2015 Article en page(s) : pp 47 - 54 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes descripteurs IGN] espace image
[Termes descripteurs IGN] méthode de Monte-Carlo par chaînes de Markov
[Termes descripteurs IGN] orthoimage
[Termes descripteurs IGN] projection orthogonale
[Termes descripteurs IGN] signalisation routièreMots-clés libres : reversible-jump Markov chain Monte Carlo Résumé : (auteur) We propose an integrated bottom-up/top-down approach to road-marking extraction from image space. It is based on energy minimization using marked point processes. A generic road marking object model enable us to define universal energy functions that handle various types of road-marking objects (dashed-lines, arrows, characters, etc.). A RJ-MCMC sampler coupled with a simulated annealing is applied to find the configuration corresponding to the minimum of the proposed energy. We used input data measurements to guide the sampler process (data driven RJ-MCMC). The approach is enhanced with a model-driven kernel using preprocessed autocorrelation and inter-correlation of road-marking templates, in order to resolve type and transformation ambiguities. The method is generic and can be applied to detect road-markings in any orthogonal view produced from optical sensors or laser scanners from aerial or terrestrial platforms. We show the results an ortho-image computed from ground-based laser scanning. Numéro de notice : A2015-758 Affiliation des auteurs : IGN (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-W4-47-2015 date de publication en ligne : 11/05/2015 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-W4-47-2015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78754
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > II-3 W4 (March 2015) . - pp 47 - 54[article]Documents numériques
en open access
Road marking extractionAdobe Acrobat PDFEccentricity in images of circular and spherical targets and its impact on spatial intersection / Thomas Luhmann in Photogrammetric record, vol 29 n° 148 (December 2014 - February 2015)
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Titre : Eccentricity in images of circular and spherical targets and its impact on spatial intersection Type de document : Article/Communication Auteurs : Thomas Luhmann, Auteur Année de publication : 2014 Article en page(s) : pp 417– 433 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes descripteurs IGN] cible réfléchissante
[Termes descripteurs IGN] déformation géométrique
[Termes descripteurs IGN] espace image
[Termes descripteurs IGN] modèle géométrique de prise de vue
[Termes descripteurs IGN] modélisation 3D
[Termes descripteurs IGN] point excentré
[Termes descripteurs IGN] projection perspectiveRésumé : (Auteur) A behaviour of perspective projection which causes eccentricity in the image measurement of circular and spherical targets is discussed. While it is commonly known that flat circular targets can have a significant displacement of the elliptical image centre with respect to the true circle centre, it can also be shown that a similar effect also exists for spherical targets. Both types of target images exhibit elliptical characteristics. If measurement methods such as best-fitting ellipses are used to detect the target, the calculated ellipse centre does not correspond to the desired target centre in 3D space. This paper firstly discusses the use and measurement of circular and spherical targets. It then describes the geometrical projection model in order to demonstrate the eccentricity in image space which, based on numerical simulations, is further quantified and investigated. Finally, the resulting effect in 3D space is estimated for stereo- and multi-image intersections. It is shown that the eccentricity is larger than usually assumed, and must be compensated for in high-accuracy applications. Furthermore, spherical targets do not display better results than circular targets. Numéro de notice : A2014-648 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12084 date de publication en ligne : 16/12/2014 En ligne : https://doi.org/10.1111/phor.12084 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75094
in Photogrammetric record > vol 29 n° 148 (December 2014 - February 2015) . - pp 417– 433[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 106-2014041 SL Revue Centre de documentation En réserve 6S (L-101) Disponible Algorithms for automatic matching of polygons or closed curves derived from different images / Y. Avrahami in SaLIS Surveying and land information science, vol 70 n° 4 (Winter 2010)
[article]
Titre : Algorithms for automatic matching of polygons or closed curves derived from different images Type de document : Article/Communication Auteurs : Y. Avrahami, Auteur ; Y. Doytsher, Auteur Année de publication : 2010 Article en page(s) : pp 175 - 185 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes descripteurs IGN] appariement d'images
[Termes descripteurs IGN] appariement de formes
[Termes descripteurs IGN] espace image
[Termes descripteurs IGN] extraction de traits caractéristiques
[Termes descripteurs IGN] itération
[Termes descripteurs IGN] points homologues
[Termes descripteurs IGN] polygone
[Termes descripteurs IGN] reconstruction 3D
[Termes descripteurs IGN] reconstruction d'image
[Termes descripteurs IGN] recouvrement d'imagesRésumé : (Auteur) Automation in 3-dimension (3D) object reconstruction is a relevant and challenging task, both from a practical and scientific point of view. This paper deals with two basic non-planar primitive objects—spatial polygons and 3D closed curves. To achieve 3D information from a pair of images, with known interior and exterior orientations, it is necessary to first extract t2D objects from each of the images separately, then match the objects to find homologues points between them, and finally reconstruct the 3D object. The matching problem between two objects derived from two different images, has a trivial solution: For each point in the first object the corresponding homologous point in the second object can be found by intersecting its epipolar line and the second object in the second image space. However, because extraction of objects in the image space is performed automatically, the process often fails. For example, when there are a number of intersections per point there is no intersection at all, or there are more points than those existing in the “real” 3D object. To overcome these difficulties, innovative algorithms designed to enable a maximal matching between polygons or closed curves and to find homologues points between them were developed. The algorithms are iterative and are based on the “overlapping criterion” between the objects. According to this criterion, projection of two polygons or closed curves from the image space to any planar surface using the real depths leads to a maximal matching between the objects. The suggested process is based on the well known optimization model called “adjustment by conditions.” One of the 2D polygons or closed curves is chosen as the static object and the other is the dynamic object. The unknowns in this model are the real depths of each point in the dynamic object. The points in the dynamic object are assigned a previously calculated average depth. In each iteration, these depths are updated until the conditional equation is optimized. During the iterations the dynamic object “slides” in the direction of the epipolar line in the image space of the static object. The “slide” rate is not constant because it depends on the varying depths of each point. The iteration process stops when the maximum overlap between the static and dynamic objects is achieved in the image space of the static object. In this paper, the algorithms, the experiments, and the results are detailed. Numéro de notice : A2010-581 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83715
in SaLIS Surveying and land information science > vol 70 n° 4 (Winter 2010) . - pp 175 - 185[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 121-2010041 SL Revue Centre de documentation Revues en salle Disponible Role of tie points in integrated sensor orientation for photogrammetric map compilation / Kourosh Khoshelham in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 3 (March 2009)
PermalinkDMC geometry analysis and virtual image characterisation / R. Alamus in Photogrammetric record, vol 23 n° 124 (December 2008 - February 2009)
PermalinkLine features between object space and image space / Jen-Jer Jaw in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 12 (December 2008)
PermalinkDevelopment and testing of a generic sensor model for pushbroom satellite imagery / T. Weser in Photogrammetric record, vol 23 n° 123 (September - November 2008)
PermalinkPotential accuracy of image orientation of small satellites: a case study of CHRIS/Proba data / Ahmed Shaker in Photogrammetric record, vol 23 n° 123 (September - November 2008)
PermalinkAutomatic determination of the optimum generic sensor model based on genetic algorithm concepts / F. Samadzadegan in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 3 (March 2005)
PermalinkAutonomous space resection using point- and line-based representation of free-form control linear features / A. Habib in Photogrammetric record, vol 18 n° 103 (September - November 2003)
PermalinkCalibration and validation of SAR interferometry for DEM generation / M. Crosetto in ISPRS Journal of photogrammetry and remote sensing, vol 57 n° 3 (December 2002 - January 2003)
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