Détail de l'auteur
Auteur Kourosh Khoshelham |
Documents disponibles écrits par cet auteur (10)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externes3D reconstruction of internal wood decay using photogrammetry and sonic tomography / Junjie Zhang in Photogrammetric record, vol 35 n° 171 (September 2020)
Titre : 3D reconstruction of internal wood decay using photogrammetry and sonic tomography Type de document : Article/Communication Auteurs : Junjie Zhang, Auteur ; Kourosh Khoshelham, Auteur Année de publication : 2020 Article en page(s) : pp 357-374 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] dépérissement
[Termes IGN] hauteur des arbres
[Termes IGN] interpolation spatiale
[Termes IGN] onde acoustique
[Termes IGN] qualité du bois
[Termes IGN] reconstruction 3D
[Termes IGN] temps de vol
[Termes IGN] tomographie
[Termes IGN] tronc
[Termes IGN] visualisation 3DRésumé : (Auteur) Knowledge of deteriorations within tree trunks is critical for arborists to conduct individual tree health assessments. Sonic tree tomography, a non‐destructive technique using sound waves, has been widely used to estimate the size and shape of internal decay based on sound wave velocity variations. However, it has commonly been applied to 2D horizontal or vertical cross sections and its accuracy is questionable due to the poor approximation of the shape of the cross section. This paper proposes an integration of close‐range photogrammetry and sonic tomography to enable accurate reconstruction of the exterior and interior of the tree trunk in 3D. The internal wood quality is represented by the spatially interpolated sound wave velocities, using the time of flight of the sound waves and the coordinates of the acoustic sensors obtained from the photogrammetric model. Experimental results show that the proposed approach provides a realistic 3D visualisation of the size, shape and location of the internal deteriorations. Numéro de notice : A2020-436 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12328 Date de publication en ligne : 06/08/2020 En ligne : https://doi.org/10.1111/phor.12328 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95842
in Photogrammetric record > vol 35 n° 171 (September 2020) . - pp 357-374[article]
Titre : BIM-PoseNet: Indoor camera localisation using a 3D indoor model and deep learning from synthetic images Type de document : Article/Communication Auteurs : Debaditya Acharya, Auteur ; Kourosh Khoshelham, Auteur ; Stephan Winter, Auteur Année de publication : 2019 Article en page(s) : pp 245 - 258 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] apprentissage profond
[Termes IGN] compréhension de l'image
[Termes IGN] estimation de pose
[Termes IGN] image de synthèse
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] positionnement en intérieur
[Termes IGN] réseau neuronal convolutif
[Termes IGN] structure-from-motionRésumé : (Auteur) The ubiquity of cameras built in mobile devices has resulted in a renewed interest in image-based localisation in indoor environments where the global navigation satellite system (GNSS) signals are not available. Existing approaches for indoor localisation using images either require an initial location or need first to perform a 3D reconstruction of the whole environment using structure-from-motion (SfM) methods, which is challenging and time-consuming for large indoor spaces. In this paper, a visual localisation approach is proposed to eliminate the requirement of image-based reconstruction of the indoor environment by using a 3D indoor model. A deep convolutional neural network (DCNN) is fine-tuned using synthetic images obtained from the 3D indoor model to regress the camera pose. Results of the experiments indicate that the proposed approach can be used for indoor localisation in real-time with an accuracy of approximately 2 m. Numéro de notice : A2019-142 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.02.020 Date de publication en ligne : 05/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.02.020 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92480
in ISPRS Journal of photogrammetry and remote sensing > vol 150 (April 2019) . - pp 245 - 258[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2019041 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019043 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019042 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt
Titre : BIM-Tracker: A model-based visual tracking approach for indoor localisation using a 3D building model Type de document : Article/Communication Auteurs : Debaditya Acharya, Auteur ; Milad Ramezani, Auteur ; Kourosh Khoshelham, Auteur ; Stephan Winter, Auteur Année de publication : 2019 Article en page(s) : pp 157 - 171 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme de Gauss-Newton
[Termes IGN] appariement de données localisées
[Termes IGN] corrélation à l'aide de traits caractéristiques
[Termes IGN] estimation de pose
[Termes IGN] filtre de Kalman
[Termes IGN] longueur focale
[Termes IGN] Matlab
[Termes IGN] méthode des moindres carrés
[Termes IGN] modèle 3D du site
[Termes IGN] positionnement en intérieur
[Termes IGN] trajet (mobilité)Résumé : (Auteur) This article presents an accurate and robust visual indoor localisation approach that not only is infrastructure-free, but also avoids accumulation error by taking advantage of (1) the widespread ubiquity of mobile devices with cameras and (2) the availability of 3D building models for most modern buildings. Localisation is performed by matching image sequences captured by a camera, with a 3D model of the building in a model-based visual tracking framework. Comprehensive evaluation of the approach with a photo-realistic synthetic dataset shows the robustness of the localisation approach under challenging conditions. Additionally, the approach is tested and evaluated on real data captured by a smartphone. The results of the experiments indicate that a localisation accuracy better than 10 cm can be achieved by using this approach. Since localisation errors do not accumulate the proposed approach is suitable for indoor localisation tasks for long periods of time and augmented reality applications, without requiring any local infrastructure. A MATLAB implementation can be found on https://github.com/debaditya-unimelb/BIM-Tracker. Numéro de notice : A2019-139 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.02.014 Date de publication en ligne : 27/02/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.02.014 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92473
in ISPRS Journal of photogrammetry and remote sensing > vol 150 (April 2019) . - pp 157 - 171[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2019041 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019043 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019042 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt
Titre : Geometric comparison and quality evaluation of 3D models of indoor environments Type de document : Article/Communication Auteurs : H. Tran, Auteur ; Kourosh Khoshelham, Auteur ; Allison Kealy, Auteur Année de publication : 2019 Article en page(s) : pp 29 - 39 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse comparative
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] erreur géométrique
[Termes IGN] espace intérieur
[Termes IGN] évaluation des données
[Termes IGN] modèle 3D du site
[Termes IGN] positionnement en intérieur
[Termes IGN] qualité des données
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] semis de points
[Termes IGN] test de performanceRésumé : (Auteur) The increasing demand for automated, cost-effective and time-efficient indoor modelling methods leads to a need for performance evaluation of these methods by assessing the quality of the reconstructed models. In this paper, we introduce a method for geometric comparison of a 3D indoor model with a reference, which is useful not only for evaluating the geometric quality of the model, but also for change detection and temporal analysis of the building. The method provides suitable criteria for the quantitative evaluation of the geometric quality in terms of completeness, correctness, and accuracy. Experimental evaluation on a synthetic dataset and the ISPRS benchmark dataset shows the potential of the proposed method for quantitative evaluation and localization of geometric errors in 3D models of indoor environments. Numéro de notice : A2019-126 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.012 Date de publication en ligne : 19/01/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.012 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92436
in ISPRS Journal of photogrammetry and remote sensing > vol 149 (March 2019) . - pp 29 - 39[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2019031 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019033 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019032 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt
Titre : Effect of slope on treetop detection using a LiDAR Canopy Height Model Type de document : Article/Communication Auteurs : Anahita Khosravipour, Auteur ; Tiejun Wang, Auteur ; Martin Isenburg, Auteur ; Kourosh Khoshelham, Auteur Année de publication : 2015 Article en page(s) : pp 44 - 52 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] houppier
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] pente
[Termes IGN] Pinus mugo subsp. uncinata
[Termes IGN] Pinus sylvestris
[Termes IGN] semis de pointsRésumé : (auteur) Canopy Height Models (CHMs) or normalized Digital Surface Models (nDSM) derived from LiDAR data have been applied to extract relevant forest inventory information. However, generating a CHM by height normalizing the raw LiDAR points is challenging if trees are located on complex terrain. On steep slopes, the raw elevation values located on either the downhill or the uphill part of a tree crown are height-normalized with parts of the digital terrain model that may be much lower or higher than the tree stem base, respectively. In treetop detection, a highest crown return located in the downhill part may prove to be a “false” local maximum that is distant from the true treetop. Based on this observation, we theoretically and experimentally quantify the effect of slope on the accuracy of treetop detection. The theoretical model presented a systematic horizontal displacement of treetops that causes tree height to be systematically displaced as a function of terrain slope and tree crown radius. Interestingly, our experimental results showed that the effect of CHM distortion on treetop displacement depends not only on the steepness of the slope but more importantly on the crown shape, which is species-dependent. The influence of the systematic error was significant for Scots pine, which has an irregular crown pattern and weak apical dominance, but not for mountain pine, which has a narrow conical crown with a distinct apex. Based on our findings, we suggest that in order to minimize the negative effect of steep slopes on the CHM, especially in heterogeneous forest with multiple species or species which change their morphological characteristics as they mature, it is best to use raw elevation values (i.e., use the un-normalized DSM) and compute the height after treetop detection. Numéro de notice : A2015-700 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.02.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.02.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78336
in ISPRS Journal of photogrammetry and remote sensing > vol 104 (June 2015) . - pp 44 - 52[article]
