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A cost-effective algorithm for calibrating multiscale geographically weighted regression models / Bo Wu in International journal of geographical information science IJGIS, vol 36 n° 5 (May 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 5 (May 2022) . - pp 898 - 917 Titre : A cost-effective algorithm for calibrating multiscale geographically weighted regression models Type de document : Article/Communication Auteurs : Bo Wu, Auteur ; Jinbiao Yan, Auteur ; Hui Lin, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 898 - 917 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse multiéchelle [Termes IGN] grande échelle [Termes IGN] hétérogénéité spatiale [Termes IGN] jeu de données [Termes IGN] modélisation spatiale [Termes IGN] régression géographiquement pondérée Résumé : (auteur) The multiscale geographically weighted regression (MGWR) model is a useful extension of the geographically weighted regression (GWR) model. MGWR, however, is a kind of Nadaraya–Watson kernel smoother, which usually leads to inaccurate estimates for the regression function and suffers from the boundary effect. Moreover, the widely used calibration technique for the MGWR with a back-fitting estimator (MGWR-BF) is computationally demanding, preventing it from being applied to large-scale data. To overcome these problems, we proposed a local linear-fitting-based MGWR (MGWR-LL) by introducing a local spatially varying coefficient model in which coefficients of different variables could be characterised as linear functions of spatial coordinates with different degrees of smoothness. Then the model was calibrated with a two-step least-squared estimated algorithm. Both simulated and actual data were implemented to validate the performance of the proposed method. The results consistently showed that the MGWR-LL automatically corrected for the boundary effect and improved the accuracy in most cases, not only in the goodness-of-fit measure but also in reducing the bias of the coefficient estimates. Moreover, the MGWR-LL significantly outperformed the MGWR-BF in computational cost, especially for larger-scale data. These results demonstrated that the proposed method can be a useful tool for the MGWR calibration. Numéro de notice : A2022-342 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1999457 Date de publication en ligne : 29/11/2021 En ligne : https://doi.org/10.1080/13658816.2021.1999457 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100516 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2022051	SL	Revue	Centre de documentation	Revues en salle	Disponible

Enhanced 3D mapping with an RGB-D sensor via integration of depth measurements and image sequences / Bo Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 9 (September 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 9 (September 2019) . - pp 633 - 642 Titre : Enhanced 3D mapping with an RGB-D sensor via integration of depth measurements and image sequences Type de document : Article/Communication Auteurs : Bo Wu, Auteur ; Xuming Ge, Auteur ; Linfu Xie, Auteur ; Wu Chen, Auteur Année de publication : 2019 Article en page(s) : pp 633 - 642 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] carte d'intérieur [Termes IGN] carte de profondeur [Termes IGN] cartographie 3D [Termes IGN] cartographie et localisation simultanées [Termes IGN] données localisées 3D [Termes IGN] état de l'art [Termes IGN] image RVB [Termes IGN] intégration de données [Termes IGN] modélisation 3D [Termes IGN] semis de points [Termes IGN] séquence d'images [Termes IGN] structure-from-motion Résumé : (Auteur) State-of-the-art visual simultaneous localization and mapping (SLAM) techniques greatly facilitate three-dimensional (3D) mapping and modeling with the use of low-cost red-green-blue-depth (RGB-D) sensors. However, the effective range of such sensors is limited due to the working range of the infra-red (IR) camera, which provides depth information, and thus the practicability of such sensors in 3D mapping and modeling is limited. To address this limitation, we present a novel solution for enhanced 3D mapping using a low-cost RGB-D sensor. We carry out state-of-the-art visual SLAM to obtain 3D point clouds within the mapping range of the RGB-D sensor and implement an improved structure-from-motion (SfM) on the collected RGB image sequences with additional constraints from the depth information to produce image-based 3D point clouds. We then develop a feature-based scale-adaptive registration to merge the gained point clouds to further generate enhanced and extended 3D mapping results. We use two challenging test sites to examine the proposed method. At these two sites, the coverage of both generated 3D models increases by more than 50% with the proposed solution. Moreover, the proposed solution achieves a geometric accuracy of about 1% in a measurement range of about 20 m. These positive experimental results not only demonstrate the feasibility and practicality of the proposed solution but also its potential. Numéro de notice : A2019-415 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.9.633 Date de publication en ligne : 01/09/2019 En ligne : https://doi.org/10.14358/PERS.85.9.633 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93542 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2019091	SL	Revue	Centre de documentation	Revues en salle	Disponible

Structural segmentation and classification of mobile laser scanning point clouds with large variations in point density / Yuan Li in ISPRS Journal of photogrammetry and remote sensing, vol 153 (July 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 153 (July 2019) . - pp 151 - 165 Titre : Structural segmentation and classification of mobile laser scanning point clouds with large variations in point density Type de document : Article/Communication Auteurs : Yuan Li, Auteur ; Bo Wu, Auteur ; Xuming Ge, Auteur Année de publication : 2019 Article en page(s) : pp 151 - 165 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] champ aléatoire conditionnel [Termes IGN] classification [Termes IGN] classification basée sur les régions [Termes IGN] densité des points [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Hong-Kong [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] Paris (75) [Termes IGN] scène urbaine [Termes IGN] segmentation en régions [Termes IGN] segmentation hiérarchique [Termes IGN] segmentation sémantique [Termes IGN] semis de points Résumé : (Auteur) Objects are formed by various structures and such structural information is essential for the identification of objects, especially for street facilities presented by mobile laser scanning (MLS) data with abundant details. However, due to the large volume of data, large variations in point density, noise and complexity of scanned scenes, the achievement of effective decomposition of objects into physical meaningful structures remains a challenge issue. And structural information has been rarely considered to improve the accuracy of distinguishing between objects with global or local similarity, such as traffic signs and traffic lights. Therefore, we propose a structural segmentation and classification method for MLS point clouds that is efficient and robust to variations in point density and complex urban scenes. During the segmentation stage, a novel region growing approach and a multi-size supervoxel segmentation algorithm robust to noise and varying density are combined to extract effective local shape descriptors. Structural components with physically meaningful labels are generated via structural labelling and clustering. During the classification stage, we consider the structural information at various scales and locations and encode it into a conditional random-field model for unary and pairwise inferences. High-order potentials are also introduced into the conditional random field to eliminate regional label noise. These high-order potentials are defined upon regions independent of connection relationships and can therefore take effect on isolated nodes. Experiments with two MLS datasets of typical urban scenes in Paris and Hong Kong were used to evaluate the performance of the proposed method. Nine and eleven different object classes were recognized from these two datasets with overall accuracies of 97.13% and 95.79%, respectively, indicating the effectiveness of the proposed method of interpreting complex urban scenes from point clouds with large variations in point density. Compared with previous studies on the Paris dataset, our method was able to recognize more classes and obtained a mean F1-score of 72.70% of seven common classes, being higher than the best of previous results. Numéro de notice : A2019-262 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.05.007 Date de publication en ligne : 28/05/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.05.007 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93075 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2019071	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2019073	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2019072	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas / Bo Wu in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 139 (May 2018) . - pp 119 - 132 Titre : Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas Type de document : Article/Communication Auteurs : Bo Wu, Auteur ; Linfu Xie, Auteur ; Han Hu, Auteur ; Qing Zhu, Auteur ; Eric Yau, Auteur Année de publication : 2018 Article en page(s) : pp 119 - 132 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] appariement d'images [Termes IGN] compensation par faisceaux [Termes IGN] Hong-Kong [Termes IGN] image aérienne oblique [Termes IGN] image terrestre [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] modélisation 3D [Termes IGN] Rhénanie du Nord-Wesphalie (Allemagne) [Termes IGN] zone urbaine Résumé : (Auteur) Photorealistic three-dimensional (3D) models are fundamental to the spatial data infrastructure of a digital city, and have numerous potential applications in areas such as urban planning, urban management, urban monitoring, and urban environmental studies. Recent developments in aerial oblique photogrammetry based on aircraft or unmanned aerial vehicles (UAVs) offer promising techniques for 3D modeling. However, 3D models generated from aerial oblique imagery in urban areas with densely distributed high-rise buildings may show geometric defects and blurred textures, especially on building façades, due to problems such as occlusion and large camera tilt angles. Meanwhile, mobile mapping systems (MMSs) can capture terrestrial images of close-range objects from a complementary view on the ground at a high level of detail, but do not offer full coverage. The integration of aerial oblique imagery with terrestrial imagery offers promising opportunities to optimize 3D modeling in urban areas. This paper presents a novel method of integrating these two image types through automatic feature matching and combined bundle adjustment between them, and based on the integrated results to optimize the geometry and texture of the 3D models generated from aerial oblique imagery. Experimental analyses were conducted on two datasets of aerial and terrestrial images collected in Dortmund, Germany and in Hong Kong. The results indicate that the proposed approach effectively integrates images from the two platforms and thereby improves 3D modeling in urban areas. Numéro de notice : A2018-112 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.03.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.03.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89542 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018051	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Integrated image matching and segmentation for 3D surface reconstruction in urban areas / Lei Ye in Photogrammetric Engineering & Remote Sensing, PERS, Vol 84 n° 3 (March 2018)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > Vol 84 n° 3 (March 2018) . - pp 135 - 148 Titre : Integrated image matching and segmentation for 3D surface reconstruction in urban areas Type de document : Article/Communication Auteurs : Lei Ye, Auteur ; Bo Wu, Auteur Année de publication : 2018 Article en page(s) : pp 135 - 148 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] appariement d'images [Termes IGN] appariement dense [Termes IGN] détection de partie cachée [Termes IGN] mesure de similitude [Termes IGN] reconstruction 3D [Termes IGN] segmentation d'image [Termes IGN] semis de points [Termes IGN] zone urbaine Résumé : (Auteur) High-resolution imagery, which features the advantages of high-quality imaging, a short revisit time, and lower costs, is an attractive option for 3D reconstruction applications. Photogrammetric 3D reconstruction requires reliable and dense image matching. In urban areas, however, image matching is particularly difficult because of the complexity of urban textures and the severe occlusion problems caused by buildings. This paper presents an integrated image matching and segmentation approach (named SATM+) for 3D reconstruction in urban areas. SATM+ is based on our existing self-adaptive triangulation-constrained matching (SATM) framework and incorporates three novel aspects to address image matching challenges in urban areas: (1) image segmentation-based occlusion filtering, (2) segment-adaptive similarity measurement to reduce matching ambiguity, and (3) local and regional dense matching propagation to generate reliable and dense matches. We performed an experimental analysis of two sets of high-resolution urban images, and the 3D point clouds generated using the proposed SATM+ were compared with airborne light detection and ranging (lidar) data and the point clouds generated using the semi-global matching (SGM) method. The results indicate that SATM+ can generate 3D point clouds with a geometric accuracy comparable to that of lidar data but a much higher point density. SATM+ performs similarly to SGM in relatively flat areas, but is superior in built-up areas. The proposed approach is a promising option for image-based 3D surface reconstruction in urban areas. Numéro de notice : A2018-137 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.3.135 Date de publication en ligne : 01/03/2018 En ligne : https://doi.org/10.14358/PERS.84.3.135 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89679 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2018031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Robust point cloud classification based on multi-level semantic relationships for urban scenes / Qing Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 129 (July 2017)  

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Uncertainty modelling and quality control for spatial data / Wenzhong Shi (2016)

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Geometric integration of high-resolution satellite imagery and airborne LiDAR data for improved geopositioning accuracy in metropolitan areas / Bo Wu in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)  

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Accuracy analysis of a dual camera system with an asymmetric photogrammetric configuration / Bo Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 3 (March 2015)  

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Adaptive geo-information processing service evolution: Reuse and local modification method / Haifeng Li in ISPRS Journal of photogrammetry and remote sensing, vol 83 (September 2013)  

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