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3D lidar point-cloud projection operator and transfer machine learning for effective road surface features detection and segmentation / Heyang Thomas Li in The Visual Computer, vol 38 n° 5 (May 2022)
[article]
Titre : 3D lidar point-cloud projection operator and transfer machine learning for effective road surface features detection and segmentation Type de document : Article/Communication Auteurs : Heyang Thomas Li, Auteur ; Zachary Todd, Auteur ; Nikolas Bielski, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1759 - 1774 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] chaîne de traitement
[Termes IGN] classification orientée objet
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] espace image
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] route
[Termes IGN] segmentation d'image
[Termes IGN] semis de points
[Termes IGN] signalisation routièreRésumé : (auteur) The classification and extraction of road markings and lanes are of critical importance to infrastructure assessment, planning and road safety. We present a pipeline for the accurate segmentation and extraction of rural road surface objects in 3D lidar point-cloud, as well as a method to extract geometric parameters belonging to tar seal. To decrease the computational resources needed, the point-clouds were aggregated into a 2D image space before being transformed using affine transformations. The Mask R-CNN algorithm is then applied to the transformed image space to localize, segment and classify the road objects. The segmentation results for road surfaces and markings can then be used for geometric parameter estimation such as road widths estimation, while the segmentation results show that the efficacy of the existing Mask R-CNN to segment needle-type objects is improved by our proposed transformations. Numéro de notice : A2022-376 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-021-02103-8 Date de publication en ligne : 28/06/2021 En ligne : https://doi.org/10.1007/s00371-021-02103-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100627
in The Visual Computer > vol 38 n° 5 (May 2022) . - pp 1759 - 1774[article]Photogrammetric determination of 3D crack opening vectors from 3D displacement fields / Frank Liebold in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)
[article]
Titre : Photogrammetric determination of 3D crack opening vectors from 3D displacement fields Type de document : Article/Communication Auteurs : Frank Liebold, Auteur ; Hans-Gerd Maas, Auteur ; Jessica Deutsch, Auteur Année de publication : 2020 Article en page(s) : pp 1 - 10 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse d'image orientée objet
[Termes IGN] détection d'objet
[Termes IGN] espace image
[Termes IGN] maillage
[Termes IGN] méthode des vecteurs de changement
[Termes IGN] mur
[Termes IGN] séquence d'images
[Termes IGN] translationMots-clés libres : fissure dans du béton Résumé : (Auteur) This publication presents a procedure for the determination of all three components of crack opening vectors from stereoscopic image sequences of a specimen under load in civil engineering material testing. The method is based on analyzing stereoscopic image sequences of a concrete specimen with a surface texture, which is suitable for applying image matching techniques. Spatio-temporal correspondences are established by applying sub-pixel accuracy area based image matching techniques to a grid of surface points. Data acquisition starts at zero load. The load is stepwise or continuously increased during the experiment. The surface points are matched between the stereo images and tracked through each camera image sequence. As an intermediate result, we obtain a set of 3D object surface points for each epoch by spatial intersection. These 3D object points are triangulated into a mesh. Then, the mesh triangles are tested for deformations by transforming the triangles into 2D space and computing the norm of the 2D relative translation vector. Connected components of deformed triangles are determined and crack normals are computed. In the next step, the 3D relative translation vector can be derived for each deformed triangle. Defining local crack opening coordinate systems for the deformed triangles, the three components of the crack opening vectors can be computed. The method has been tested and validated in practical experiments. The technique is capable of quantitatively analyzing cracks with a width of less than one pixel in image space. Numéro de notice : A2020-172 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.03.019 Date de publication en ligne : 08/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.03.019 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94876
in ISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 1 - 10[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020061 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020063 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020062 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Absolute orientation based on line coordinates / Qing H. Sheng in Photogrammetric record, vol 32 n° 157 (March - May 2017)
[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 IGN] contour
[Termes IGN] coordonnées géographiques
[Termes IGN] espace image
[Termes IGN] espace objet
[Termes IGN] géoréférencement direct
[Termes IGN] orientation absolue
[Termes IGN] point d'appui
[Termes IGN] segment de droite
[Termes 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 DOI : 10.1111/phor.12178 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)
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 IGN] caméra numérique
[Termes IGN] carte d'intérieur
[Termes IGN] espace image
[Termes IGN] espace objet
[Termes IGN] Kinect
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] semis de pointsRésumé : (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 DOI : 10.18419/opus-3988 En ligne : http://doi.org/10.18419/opus-3988 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85007 Road marking extraction using a model&data-driven RJ-MCMC / Alexandre Hervieu in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W4 (March 2015)
[article]
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 Année de publication : 2015 Conférence : ISPRS 2015, PIA 2015 - HRIGI 2015 Joint ISPRS conference 25/03/2015 27/03/2015 Munich Allemagne ISPRS OA Annals Article en page(s) : pp 47 - 54 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] espace image
[Termes IGN] méthode de Monte-Carlo par chaînes de Markov
[Termes IGN] orthoimage
[Termes IGN] projection orthogonale
[Termes 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 : LASTIG MATIS (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 > vol II-3 W4 (March 2015) . - pp 47 - 54[article]Documents numériques
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