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Auteur Stuart Robson |
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Automatic sensor orientation using horizontal and vertical line feature constraints / Yanbiao Sun in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)
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Titre : Automatic sensor orientation using horizontal and vertical line feature constraints Type de document : Article/Communication Auteurs : Yanbiao Sun, Auteur ; Stuart Robson, Auteur ; Daniel Scott, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 172 - 184 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] angle azimutal
[Termes IGN] angle vertical
[Termes IGN] compensation par faisceaux
[Termes IGN] coordonnées horizontales
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] forme linéaire
[Termes IGN] image aérienne
[Termes IGN] ligne caractéristique
[Termes IGN] orientation d'image
[Termes IGN] orientation du capteur
[Termes IGN] point d'appuiRésumé : (Auteur) To improve the accuracy of sensor orientation using calibrated aerial images, this paper proposes an automatic sensor orientation method utilizing horizontal and vertical constraints on human-engineered structures, addressing the limitations faced with sub-optimal number of Ground Control Points (GCPs) within a scene. Related state-of-the-art methods rely on structured building edges, and necessitate manual identification of end points. Our method makes use of line-segments but eliminates the need for these matched end points, thus eliminating the need for inefficient manual intervention.
To achieve this, a 3D line in object space is represented by the intersection of two planes going through two camera centers. The normal vector of each plane can be written as a function of a pair of azimuth and elevations angles. The normal vector of the 3D line can be expressed by the cross product of these two plane’s normal vectors. Then, we create observation functions of horizontal and vertical line constraints based on the zero-vector cross-product and the dot-product of the normal vector of the 3D lines. The observation functions of the horizontal and vertical lines are then introduced into a hybrid Bundle Adjustment (BA) method as constraints, including observed image points as well as observed line segment projections. Finally, to assess the feasibility and effectiveness of the proposed method, simulated and real data are tested. The results demonstrate that, in cases with only 3 GCPs, the accuracy of the proposed method utilizing line features extracted automatically, is increased by 50%, compared to a BA using only point constraints.Numéro de notice : A2019-140 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.02.011 Date de publication en ligne : 28/02/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.02.011 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92478
in ISPRS Journal of photogrammetry and remote sensing > vol 150 (April 2019) . - pp 172 - 184[article]Réservation
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Titre : Close-range photogrammetry and 3D imaging Type de document : Guide/Manuel Auteurs : Thomas Luhmann, Auteur ; Stuart Robson, Auteur ; Stephen Kyle, Auteur ; Jan Böhm , Auteur
Editeur : Berlin, New York : Walter de Gruyter Année de publication : 2019 Importance : 822 p. Format : 17 x 24 cm ISBN/ISSN/EAN : 978-3-11-060724-6 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] analyse d'image numérique
[Termes IGN] étalonnage
[Termes IGN] image 3D
[Termes IGN] instrument de photogrammétrie
[Termes IGN] logiciel de photogrammétrie
[Termes IGN] modélisation 3D
[Termes IGN] orientation d'image
[Termes IGN] photogrammétrie métrologique
[Termes IGN] précision des mesures
[Termes IGN] reconstruction 3D
[Termes IGN] transformation mathématiqueIndex. décimale : 33.30 Photogrammétrie numérique Résumé : (Editeur) This is the third edition of the well-known guide to close-range photogrammetry. It provides a thorough presentation of the methods, mathematics, systems and applications which comprise the subject of close-range photogrammetry, which uses accurate imaging techniques to analyse the three-dimensional shape of a wide range of manufactured and natural objects. Note de contenu : 1. Introduction
2. Mathematical fundamentals
3. Imaging technology
4. Analytical methods
5. Digital image analysis
6. Measuring tasks and systems
7. Measurement design and quality
8. Example applicationsNuméro de notice : 26341 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Manuel de cours DOI : 10.1515/9783110607253 En ligne : https://doi.org/10.1515/9783110607253 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95700 A comparison of dense matching algorithms for scaled surface reconstruction using stereo camera rigs / Ali Hosseininaveh Ahmadabadian in ISPRS Journal of photogrammetry and remote sensing, vol 78 (April 2013)
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[article]
Titre : A comparison of dense matching algorithms for scaled surface reconstruction using stereo camera rigs Type de document : Article/Communication Auteurs : Ali Hosseininaveh Ahmadabadian, Auteur ; Stuart Robson, Auteur ; Johannes Böhm , Auteur
Année de publication : 2013 Article en page(s) : pp 157 - 167 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] appariement d'images
[Termes IGN] appariement dense
[Termes IGN] caméra numérique
[Termes IGN] compensation par faisceaux
[Termes IGN] contrainte géométrique
[Termes IGN] espace objet
[Termes IGN] MicMac
[Termes IGN] photogrammétrie métrologique
[Termes IGN] précision stéréoscopique
[Termes IGN] reconstruction 3D
[Termes IGN] reconstruction d'objet
[Termes IGN] semis de points
[Termes IGN] structure-from-motionRésumé : (Auteur) Photogrammetric methods for dense 3D surface reconstruction are increasingly available to both professional and amateur users who have requirements that span a wide variety of applications. One of the key concerns in choosing an appropriate method is to understand the achievable accuracy and how choices made within the workflow can alter that outcome. In this paper we consider accuracy in two components: the ability to generate a correctly scaled 3D model; and the ability to automatically deliver a high quality data set that provides good agreement to a reference surface. The determination of scale information is particularly important, since a network of images usually only provides angle measurements and thus leads to unscaled geometry. A solution is the introduction of known distances in object space, such as base lines between camera stations or distances between control points. In order to avoid using known object distances, the method presented in this paper exploits a calibrated stereo camera utilizing the calibrated base line information from the camera pair as an observational based geometric constraint. The method provides distance information throughout the object volume by orbiting the object. In order to test the performance of this approach, four topical surface matching methods have been investigated to determine their ability to produce accurate, dense point clouds. The methods include two versions of Semi-Global Matching as well as MicMac and Patch-based Multi-View Stereo (PMVS). These methods are implemented on a set of stereo images captured from four carefully selected objects by using (1) an off-the-shelf low cost 3D camera and (2) a pair of Nikon D700 DSLR cameras rigidly mounted in close proximity to each other. Inter-comparisons demonstrate the subtle differences between each of these permutations. The point clouds are also compared to a dataset obtained with a Nikon MMD laser scanner. Finally, the established process of achieving accurate point clouds from images and known object space distances are compared with the presented strategies. Results from the matching demonstrate that if a good imaging network is provided, using a stereo camera and bundle adjustment with geometric constraints can effectively resolve the scale. Among the strategies for dense 3D reconstruction, using the presented method for solving the scale problem and PMVS on the images captured with two DSLR cameras resulted in a dense point cloud as accurate as the Nikon laser scanner dataset. Numéro de notice : A2013-184 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.01.015 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.01.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32322
in ISPRS Journal of photogrammetry and remote sensing > vol 78 (April 2013) . - pp 157 - 167[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2013041 RAB Revue Centre de documentation En réserve L003 Disponible