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Co‐registration of panoramic mobile mapping images and oblique aerial images / Phillipp Jende in Photogrammetric record, vol 34 n° 166 (June 2019)  

Public [article]  inPhotogrammetric record > vol 34 n° 166 (June 2019) . - pp 148 - 173 Titre : Co‐registration of panoramic mobile mapping images and oblique aerial images Type de document : Article/Communication Auteurs : Phillipp Jende, Auteur ; Francesco Nex, Auteur ; M. George Vosselman, Auteur ; Markus Gerke, Auteur Année de publication : 2019 Article en page(s) : pp 148 - 173 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] façade [Termes descripteurs IGN] image aérienne oblique [Termes descripteurs IGN] image panoramique [Termes descripteurs IGN] image terrestre [Termes descripteurs IGN] point d'appui [Termes descripteurs IGN] semis de points clairsemés [Termes descripteurs IGN] superposition d'images Résumé : (Auteur) Mobile mapping relies on satellite‐based positioning, which suffers from line‐of‐sight and multipath issues. As an alternative, this paper presents a fully automatic approach for the co‐registration of mobile mapping and oblique aerial images to introduce highly accurate and reliable ground control for mobile mapping data adjustment. An oblique view of a scene introduces similarities as well as challenges regarding co‐registration with mobile mapping images, which is supported by mutual planes in both datasets. Façade planes from a sparse point cloud are used as projection surfaces for the mobile mapping and aerial datasets, overcoming large perspective differences between them to simplify the registration. The performance of the procedure indicates an inlier rate of around 80%. Numéro de notice : A2019-245 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12276 date de publication en ligne : 29/04/2019 En ligne : https://doi.org/10.1111/phor.12276 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92956 [article]

A fully automatic approach to register mobile mapping and airborne imagery to support the correction of plateform trajectories in GNSS-denied urban areas / Phillipp Jende in ISPRS Journal of photogrammetry and remote sensing, vol 141 (July 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 141 (July 2018) . - pp 86 - 99 Titre : A fully automatic approach to register mobile mapping and airborne imagery to support the correction of plateform trajectories in GNSS-denied urban areas Type de document : Article/Communication Auteurs : Phillipp Jende, Auteur ; Francesco Nex, Auteur ; Markus Gerke, Auteur ; M. George Vosselman, Auteur Année de publication : 2018 Article en page(s) : pp 86 - 99 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] appariement géométrique [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] filtre de Wallis [Termes descripteurs IGN] GNSS assisté pour la navigation [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] image terrestre [Termes descripteurs IGN] orientation d'image [Termes descripteurs IGN] orthoimage [Termes descripteurs IGN] point d'appui [Termes descripteurs IGN] précision décimétrique [Termes descripteurs IGN] système de numérisation mobile [Termes descripteurs IGN] zone urbaine Résumé : (Auteur) Mobile Mapping (MM) solutions have become a significant extension to traditional data acquisition methods over the last years. Independently from the sensor carried by a platform, may it be laser scanners or cameras, high-resolution data postings are opposing a poor absolute localisation accuracy in urban areas due to GNSS occlusions and multipath effects. Potentially inaccurate position estimations are propagated by IMUs which are furthermore prone to drift effects. Thus, reliable and accurate absolute positioning on a par with MM's high-quality data remains an open issue. Multiple and diverse approaches have shown promising potential to mitigate GNSS errors in urban areas, but cannot achieve decimetre accuracy, require manual effort, or have limitations with respect to costs and avail-ability. This paper presents a fully automatic approach to support the correction of MM imaging data based on correspondences with airborne nadir images. These correspondences can be employed to correct the MM plat-form's orientation by an adjustment solution. Unlike MM as such, aerial images do not suffer from GNSS oc-clusions, and their accuracy is usually verified by employing well-established methods using ground control points. However, a registration between MM and aerial images is a non-standard matching scenario, and requires several strategies to yield reliable and accurate correspondences. Scale, perspective and content strongly vary between both image sources, thus traditional feature matching methods may fail. To this end, the registration process is designed to focus on common and clearly distinguishable elements, such as road markings, manholes, or kerbstones. With a registration accuracy of about 98%, reliable tie information between MM and aerial data can be derived. Even though, the adjustment strategy is not covered in its entirety in this paper, accuracy results after adjustment will be presented. It will be shown that a decimetre accuracy is well achievable in a real data test scenari Numéro de notice : A2018-285 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.04.017 date de publication en ligne : 30/04/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.04.017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90397 [article]

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Skeletal camera network embedded structure-from-motion for 3D scene reconstruction from UAV images / Zhihua Xua in ISPRS Journal of photogrammetry and remote sensing, vol 121 (November 2016)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 121 (November 2016) . - pp 113 - 127 Titre : Skeletal camera network embedded structure-from-motion for 3D scene reconstruction from UAV images Type de document : Article/Communication Auteurs : Zhihua Xua, Auteur ; Lixin Wud, Auteur ; Markus Gerke, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 113 - 127 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes descripteurs IGN] appariement de points [Termes descripteurs IGN] connexité (topologie) [Termes descripteurs IGN] drone [Termes descripteurs IGN] prise de vue aérienne [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] squelettisation [Termes descripteurs IGN] structure-from-motion [Termes descripteurs IGN] topologie Résumé : (Auteur) Structure-from-Motion (SfM) techniques have been widely used for 3D scene reconstruction from multi-view images. However, due to the large computational costs of SfM methods there is a major challenge in processing highly overlapping images, e.g. images from unmanned aerial vehicles (UAV). This paper embeds a novel skeletal camera network (SCN) into SfM to enable efficient 3D scene reconstruction from a large set of UAV images. First, the flight control data are used within a weighted graph to construct a topologically connected camera network (TCN) to determine the spatial connections between UAV images. Second, the TCN is refined using a novel hierarchical degree bounded maximum spanning tree to generate a SCN, which contains a subset of edges from the TCN and ensures that each image is involved in at least a 3-view configuration. Third, the SCN is embedded into the SfM to produce a novel SCN-SfM method, which allows performing tie-point matching only for the actually connected image pairs. The proposed method was applied in three experiments with images from two fixed-wing UAVs and an octocopter UAV, respectively. In addition, the SCN-SfM method was compared to three other methods for image connectivity determination. The comparison shows a significant reduction in the number of matched images if our method is used, which leads to less computational costs. At the same time the achieved scene completeness and geometric accuracy are comparable. Numéro de notice : A2016--016 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.08.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83878 [article]

vol 93 - July 2014 - Urban object extraction (Bulletin de ISPRS Journal of photogrammetry and remote sensing) / Franz Rottensteiner  

Public [n° ou bulletin]  est un bulletin de ISPRS Journal of photogrammetry and remote sensing / International society for photogrammetry and remote sensing (1990 - )   Titre : vol 93 - July 2014 - Urban object extraction Type de document : Périodique Auteurs : Franz Rottensteiner, Editeur scientifique ; Gunho Sohn, Editeur scientifique ; International society for photogrammetry and remote sensing, Auteur ; Markus Gerke, Editeur scientifique ; Jan Dirk Wegner, Editeur scientifique Année de publication : 2014 Importance : 270 p. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie Numéro de notice : 081-201407 Thématique : IMAGERIE Nature : Numéro de périodique En ligne : http://www.sciencedirect.com/science/journal/09242716/93 Format de la ressource électronique : URL sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=17328 [n° ou bulletin]

Contient

• A review of ground-based SAR interferometry for deformation measurement / Oriol Monserrat in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)  
• Land cover classification of finer resolution remote sensing data integrating temporal features from time series coarser resolution data / Kun Jia in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
• Calibration of area based diameter distribution with individual tree based diameter estimates using airborne laser scanning / Qing Xu in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
• Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing / Jaime Zabalza in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
• SAR change detection based on intensity and texture changes / Maoguo Gong in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
• Discontinuous GBSAR deformation monitoring / Michele Crosetto in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
• Ground and building extraction from LiDAR data based on differential morphological profiles and locally fitted surfaces / Domen Mongus in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
• Context-based automatic reconstruction and texturing of 3D urban terrain for quick-response tasks / Dimitri Bolatov in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
• Automatic representation and reconstruction of DBM from LiDAR data using Recursive Minimum Bounding Rectangle / Eunju Kwak in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
• A graph edit dictionary for correcting errors in roof topology graphs reconstructed from point clouds / B. Xiong in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
• Detection, segmentation and classification of 3D urban objects using mathematical morphology and supervised learning / Andrès Serna in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)

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Fusion of airborne laserscanning point clouds and images for supervised and unsupervised scene classification / Markus Gerke in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 78 - 92 Titre : Fusion of airborne laserscanning point clouds and images for supervised and unsupervised scene classification Type de document : Article/Communication Auteurs : Markus Gerke, Auteur ; Jing Xiao, Auteur Année de publication : 2014 Article en page(s) : pp 78 - 92 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] champ aléatoire de Markov [Termes descripteurs IGN] classification dirigée [Termes descripteurs IGN] classification non dirigée [Termes descripteurs IGN] classification par arbre de décision [Termes descripteurs IGN] conflation [Termes descripteurs IGN] densification [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] toit [Termes descripteurs IGN] voxel Résumé : (Auteur) Automatic urban object detection from airborne remote sensing data is essential to process and efficiently interpret the vast amount of airborne imagery and Laserscanning (ALS) data available today. This paper combines ALS data and airborne imagery to exploit both: the good geometric quality of ALS and the spectral image information to detect the four classes buildings, trees, vegetated ground and sealed ground. A new segmentation approach is introduced which also makes use of geometric and spectral data during classification entity definition. Geometric, textural, low level and mid level image features are assigned to laser points which are quantified into voxels. The segment information is transferred to the voxels and those clusters of voxels form the entity to be classified. Two classification strategies are pursued: a supervised method, using Random Trees and an unsupervised approach, embedded in a Markov Random Field framework and using graph-cuts for energy optimization. A further contribution of this paper concerns the image-based point densification for building roofs which aims to mitigate the accuracy problems related to large ALS point spacing. Results for the ISPRS benchmark test data show that to rely on color information to separate vegetation from non-vegetation areas does mostly lead to good results, but in particular in shadow areas a confusion between classes might occur. The unsupervised classification strategy is especially sensitive in this respect. As far as the point cloud densification is concerned, we observe similar sensitivity with respect to color which makes some planes to be missed out, or false detections still remain. For planes where the densification is successful we see the expected enhancement of the outline. Numéro de notice : A2014-014 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32919 [article]

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