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Ancient Chinese architecture 3D preservation by merging ground and aerial point clouds / Xiang Gao in ISPRS Journal of photogrammetry and remote sensing, vol 143 (September 2018)
[article]
Titre : Ancient Chinese architecture 3D preservation by merging ground and aerial point clouds Type de document : Article/Communication Auteurs : Xiang Gao, Auteur ; Shuhan Shen, Auteur ; Yang Zhou, Auteur ; Hainan Cui, Auteur ; Lingjie Zhu, Auteur ; Zhanyi Hu, Auteur Année de publication : 2018 Article en page(s) : pp 72 - 84 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] architecture
[Termes IGN] données localisées 3D
[Termes IGN] fusion de données
[Termes IGN] image aérienne
[Termes IGN] image terrestre
[Termes IGN] modèle 3D du site
[Termes IGN] patrimoine immobilier
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] semis de points
[Termes IGN] templeRésumé : (Auteur) Ancient Chinese architecture 3D digitalization and documentation is a challenging task for the image based modeling community due to its architectural complexity and structural delicacy. Currently, an effective approach to ancient Chinese architecture 3D reconstruction is to merge the two point clouds, separately obtained from ground and aerial images by the SfM technique. There are two understanding issues should be specially addressed: (1) it is difficult to find the point matches between the images from different sources due to their remarkable variations in viewpoint and scale; (2) due to the inevitable drift phenomenon in any SfM reconstruction process, the resulting two point clouds are no longer strictly related by a single similarity transformation as it should be theoretically. To address these two issues, a new point cloud merging method is proposed in this work. Our method has the following characteristics: (1) the images are matched by leveraging sparse mesh based image synthesis; (2) the putative point matches are filtered by geometrical consistency check and geometrical model verification; and (3) the two point clouds are merged via bundle adjustment by linking the ground-to-aerial tracks. Extensive experiments show that our method outperforms many of the state-of-the-art approaches in terms of ground-to-aerial image matching and point cloud merging. Numéro de notice : A2018-355 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.04.023 Date de publication en ligne : 08/05/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.04.023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90589
in ISPRS Journal of photogrammetry and remote sensing > vol 143 (September 2018) . - pp 72 - 84[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018091 RAB Livre Centre de documentation En réserve L003 Disponible 081-2018093 DEP-EXM Livre LASTIG Dépôt en unité Exclu du prêt 081-2018092 DEP-EAF Livre Nancy Dépôt en unité Exclu du prêt Extraction of building roof planes with stratified random sample consensus / André C. Carrilho in Photogrammetric record, vol 33 n° 163 (September 2018)
[article]
Titre : Extraction of building roof planes with stratified random sample consensus Type de document : Article/Communication Auteurs : André C. Carrilho, Auteur ; Mauricio Galo, Auteur Année de publication : 2018 Article en page(s) : pp 363 - 380 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] morphologie mathématique
[Termes IGN] Ransac (algorithme)
[Termes IGN] semis de points
[Termes IGN] toit
[Termes IGN] varianceRésumé : (Auteur) This paper describes a consensus‐set estimation for building roof‐plane detection using a stratified random sample consensus (sRANSAC) algorithm applied to point clouds acquired by laser scanning systems. The main idea is to use one initial classification to generate consensus‐set candidates to optimise the sampling mechanism compared to the original RANSAC. The initial classification is performed using mathematical morphology to filter ground returns and estimate local variance information to detect potential planar regions. Thus, the algorithm can prioritise points within planar segments and the number of iterations can be estimated dynamically from available data. The results based on experiments using five different lidar datasets indicate that the proposed method reduces the number of computations for building roof‐plane detection and also improves accuracy compared to RANSAC. Numéro de notice : A2018-620 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12254 Date de publication en ligne : 21/09/2018 En ligne : https://doi.org/10.1111/phor.12254 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92864
in Photogrammetric record > vol 33 n° 163 (September 2018) . - pp 363 - 380[article]Les peintures murales des lieux de culte du Sud de l’arc alpin du XIVe au XVIe siècle / Océane Acquier in Géomatique expert, n° 124 (septembre - octobre 2018)
[article]
Titre : Les peintures murales des lieux de culte du Sud de l’arc alpin du XIVe au XVIe siècle Type de document : Article/Communication Auteurs : Océane Acquier, Auteur ; Gourguen Davtian, Auteur ; Antoine Pasqualini, Auteur ; Sabine Sorin, Auteur ; Rosa-Maria Dessì, Auteur Année de publication : 2018 Article en page(s) : pp 35 - 40 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] Alpes (France)
[Termes IGN] base de données thématiques
[Termes IGN] écriture
[Termes IGN] église
[Termes IGN] Italie
[Termes IGN] peintureRésumé : (éditeur) Entre le XIVe et le XVIe siècle, les églises de la partie méridionale des Alpes, aussi bien sur le versant français qu’italien, ont vu fleurir une série de peintures murales accompagnées d’inscriptions. Comment cette pratique s’organise-t-elle spatialement, et quelles sont les conclusions que l’on peut en tirer sur ce mouvement artistique singulier ? Numéro de notice : A2018-422 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90892
in Géomatique expert > n° 124 (septembre - octobre 2018) . - pp 35 - 40[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité IFN-001-P002084 PER Revue Nogent-sur-Vernisson Salle périodiques Exclu du prêt Three-dimensional building façade segmentation and opening area detection from point clouds / S.M. Iman Zolanvari in ISPRS Journal of photogrammetry and remote sensing, vol 143 (September 2018)
[article]
Titre : Three-dimensional building façade segmentation and opening area detection from point clouds Type de document : Article/Communication Auteurs : S.M. Iman Zolanvari, Auteur ; Debra F. Laefer, Auteur ; Atteyeh S. Natanzi, Auteur Année de publication : 2018 Article en page(s) : pp 134 - 149 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] toitRésumé : (Auteur) Laser scanning generates a point cloud from which geometries can be extracted, but most methods struggle to do this automatically, especially for the entirety of an architecturally complex building (as opposed to that of a single façade). To address this issue, this paper introduces the Improved Slicing Method (ISM), an innovative and computationally-efficient method for three-dimensional building segmentation. The method is also able to detect opening boundaries even on roofs (e.g. chimneys), as well as a building’s overall outer boundaries using a local density analysis technique. The proposed procedure is validated by its application to two architecturally complex, historic brick buildings. Accuracies of at least 86% were achieved, with computational times as little as 0.53 s for detecting features from a data set of 5.0 million points. The accuracy more than rivalled the current state of the art, while being up to six times faster and with the further advantage of requiring no manual intervention or reliance on a priori information. Numéro de notice : A2018-358 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.04.004 Date de publication en ligne : 09/05/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.04.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90592
in ISPRS Journal of photogrammetry and remote sensing > vol 143 (September 2018) . - pp 134 - 149[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018091 RAB Livre Centre de documentation En réserve L003 Disponible 081-2018093 DEP-EXM Livre LASTIG Dépôt en unité Exclu du prêt 081-2018092 DEP-EAF Livre Nancy Dépôt en unité Exclu du prêt Evolutionary approach for detection of buried remains using hyperspectral images / Leon Dozal in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 7 (juillet 2018)
[article]
Titre : Evolutionary approach for detection of buried remains using hyperspectral images Type de document : Article/Communication Auteurs : Leon Dozal, Auteur ; José L. Silvan-Cardenas, Auteur ; Daniela Moctezuma, Auteur ; Oscar S. Siordia, Auteur ; Enrique Naredo, Auteur Année de publication : 2018 Article en page(s) : pp 435 - 450 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme génétique
[Termes IGN] image hyperspectrale
[Termes IGN] Mexique
[Termes IGN] précision de la classification
[Termes IGN] teneur en eau de la végétation
[Termes IGN] tombeRésumé : (Auteur) Hyperspectral imaging has been successfully utilized to locate clandestine graves. This study applied a Genetic Programming technique called Brain Programming (BP) for automating the design of Hyperspectral Visual Attention Models (H-VAM.), which is proposed as a new method for the detection of buried remains. Four graves were simulated and monitored during six months by taking in situ spectral measurements of the ground. Two experiments were implemented using Kappa and weighted Kappa coefficients as classification accuracy measures for guiding the BP search of the best H-VAM. Experimental results demonstrate that the proposed BP method improves classification accuracy compared to a previous approach. A better detection performance was observed for the image acquired after three months from burial. Moreover, results suggest that the use of spectral bands that respond to vegetation and water content of the plants and provide evidence that the number of buried bodies plays a crucial role on a successful detection. Numéro de notice : A2018-359 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.7.435 Date de publication en ligne : 01/07/2018 En ligne : https://doi.org/10.14358/PERS.84.7.435 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90599
in Photogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 7 (juillet 2018) . - pp 435 - 450[article]Réservation
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