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Detecting and characterizing downed dead wood using terrestrial laser scanning / Tuomas Yrttimaa in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 76 - 90 Titre : Detecting and characterizing downed dead wood using terrestrial laser scanning Type de document : Article/Communication Auteurs : Tuomas Yrttimaa, Auteur ; Ninni Saarinen, Auteur ; Ville Luoma, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 76 - 90 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] bois mort [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] Finlande [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] inventaire forestier étranger (données) [Termes descripteurs IGN] placette d'échantillonnage [Termes descripteurs IGN] qualité des données [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] rastérisation [Termes descripteurs IGN] segmentation [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] tronc [Termes descripteurs IGN] volume en bois Résumé : (Auteur) Dead wood is a key forest structural component for maintaining biodiversity and storing carbon. Despite its important role in a forest ecosystem, quantifying dead wood alongside standing trees has often neglected when investigating the feasibility of terrestrial laser scanning (TLS) in forest inventories. The objective of this study was therefore to develop an automatic method for detecting and characterizing downed dead wood with a diameter exceeding 5 cm using multi-scan TLS data. The developed four-stage algorithm included (1) RANSAC-cylinder filtering, (2) point cloud rasterization, (3) raster image segmentation, and (4) dead wood trunk positioning. For each detected trunk, geometry-related quality attributes such as dimensions and volume were automatically determined from the point cloud. For method development and validation, reference data were collected from 20 sample plots representing diverse southern boreal forest conditions. Using the developed method, the downed dead wood trunks were detected with an overall completeness of 33% and correctness of 76%. Up to 92% of the downed dead wood volume were detected at plot level with mean value of 68%. We were able to improve the detection accuracy of individual trunks with visual interpretation of the point cloud, in which case the overall completeness was increased to 72% with mean proportion of detected dead wood volume of 83%. Downed dead wood volume was automatically estimated with an RMSE of 15.0 m3/ha (59.3%), which was reduced to 6.4 m3/ha (25.3%) as visual interpretation was utilized to aid the trunk detection. The reliability of TLS-based dead wood mapping was found to increase as the dimensions of dead wood trunks increased. Dense vegetation caused occlusion and reduced the trunk detection accuracy. Therefore, when collecting the data, attention must be paid to the point cloud quality. Nevertheless, the results of this study strengthen the feasibility of TLS-based approaches in mapping biodiversity indicators by demonstrating an improved performance in quantifying ecologically most valuable downed dead wood in diverse forest conditions. Numéro de notice : A2019-205 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.03.007 date de publication en ligne : 16/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.03.007 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92668 [article]

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Fusion of thermal imagery with point clouds for building façade thermal attribute mapping / Dong Lin in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 162 - 175 Titre : Fusion of thermal imagery with point clouds for building façade thermal attribute mapping Type de document : Article/Communication Auteurs : Dong Lin, Auteur ; Malgorzata Jarząbek-Rychard, Auteur ; Xiaochong Tong, Auteur ; Hans-Gerd Maas, Auteur Année de publication : 2019 Article en page(s) : pp 162 - 175 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] façade [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] image thermique [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] SIFT (algorithme) [Termes descripteurs IGN] texturage Résumé : (Auteur) Thermal image data are widely used to assess the insulation quality of buildings and to detect thermal leakages. In our approach, we merge terrestrial thermal image data and 3D point clouds to perform thermal texture mapping for building facades. Since geo-referencing data of a hand-held thermal camera is usually not available in such applications, registration between thermal images and a 3D point cloud (for instance generated from RGB image data by structure-from-motion techniques) is essential. In our approach, thermal image data registration is conducted in four steps: First, another point cloud is generated from the thermal image data. Next, a coarse registration between thermal point cloud and RGB point cloud is performed using the fast global registration (FGR) algorithm. The best corresponding thermal-RGB image pairs are acquired by picking up the lowest Euclidean distance between the exterior orientation parameters of thermal images and transformed exterior orientation parameters of RGB images. Subsequently, radiation-invariant feature transform (RIFT), normalized barycentric coordinate system (NBCS) and random sample consensus (RANSAC) are employed to extract reliable matching features on thermal-RGB image pairs. Afterwards, a fine registration is performed by mono-plotting of the RGB image, followed by image resection of the thermal image. Finally, in terms of texture mapping algorithms, in order to remove the blur effects caused by small misalignments for different candidate images, a global image pose refinement approach, which aims to minimize the temperature disagreements provided by different images for the same object points, is proposed. In addition, in order to ensure high geometric and radiant accuracy, camera calibrations are performed. Experiments showed that the proposed method could not only achieve high geometric registration accuracy, but also provide a good radiometric accuracy with RMSE lower than 1.5 °C. Numéro de notice : A2019-208 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.03.010 date de publication en ligne : 21/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.03.010 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92674 [article]

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Pairwise coarse registration of point clouds in urban scenes using voxel-based 4-planes congruent sets / Yusheng Xu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 106 - 123 Titre : Pairwise coarse registration of point clouds in urban scenes using voxel-based 4-planes congruent sets Type de document : Article/Communication Auteurs : Yusheng Xu, Auteur ; Richard Boerner, Auteur ; Wei Yao, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 106 - 123 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] congruence [Termes descripteurs IGN] données 4D [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] modèle stéréoscopique [Termes descripteurs IGN] octree [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] scène urbaine [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] surface plane [Termes descripteurs IGN] voxel Résumé : (Auteur) To ensure complete coverage when measuring a large-scale urban area, pairwise registration between point clouds acquired via terrestrial laser scanning or stereo image matching is usually necessary when there is insufficient georeferencing information from additional GNSS and INS sensors. In this paper, we propose a semi-automatic and target-less method for coarse registration of point clouds using geometric constraints of voxel-based 4-plane congruent sets (V4PCS). The planar patches are firstly extracted from voxelized point clouds. Then, the transformation invariant, 4-plane congruent sets are constructed from extracted planar surfaces in each point cloud. Initial transformation parameters between point clouds are estimated via corresponding congruent sets having the highest registration scores in the RANSAC process. Finally, a closed-form solution is performed to achieve optimized transformation parameters by finding all corresponding planar patches using the initial transformation parameters. Experimental results reveal that our proposed method can be effective for registering point clouds acquired from various scenes. A success rate of better than 80% was achieved, with average rotation errors of about 0.5 degrees and average translation errors less than approximately 0.6 m. In addition, our proposed method is more efficient than other baseline methods when using the same hardware and software configuration conditions. Numéro de notice : A2019-207 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.02.015 date de publication en ligne : 18/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.02.015 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92673 [article]

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Measuring stem diameters with TLS in boreal forests by complementary fitting procedure / Timo P Pitkänen in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 147 (January 2019) . - pp 294 - 306 Titre : Measuring stem diameters with TLS in boreal forests by complementary fitting procedure Type de document : Article/Communication Auteurs : Timo P Pitkänen, Auteur ; Pasi Raumonen, Auteur ; Annika S. Kangas, Auteur Année de publication : 2019 Article en page(s) : pp 294 - 306 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] calcul automatique [Termes descripteurs IGN] chaîne de traitement [Termes descripteurs IGN] diamètre des arbres [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] extraction d'arbres [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] itération [Termes descripteurs IGN] méthode de mesure [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] télémétrie laser terrestre [Termes descripteurs IGN] tronc Résumé : (auteur) Point clouds generated by terrestrial laser scanners (TLS) have enabled new ways to measure stem diameters. A common method for diameter calculation is to fit cylindrical or circular shapes into the TLS point cloud, which can be based either on a single scan or a co-registered combination of several scans. However, as various defects in the point cloud may affect the final diameter results, we propose an automatized processing chain which takes advantage of complementing steps. Processing consists of two fitting phases and an additional taper curve calculation to define the final diameter measurements. First, stems are detected from co-registered data of several scans using surface normals and cylinder fitting. This provides a robust framework for localizing the stems and estimating diameters at various heights. Then, guided by the cylinders and their indicative diameters, another fitting round is performed by cutting the stems into thin horizontal slices and reassessing their diameters by circular shape. For each slice, the quality of the cylinder-modelled diameter is evaluated first with co-registered data and if it is found to be deficient, potentially due to modelling defects or co-registration errors, diameter is detected through single scans. Finally, slice diameters are applied to construct a spline-based taper curve model for each tree, which is used to calculate the final stem dimensions. This methodology was tested in southern Finland using a set of 505 trees. At the breast height level (1.3 m), the results indicate 5.2 mm mean difference (3.2%), −0.4 mm bias (-0.3%) and 7.3 mm root mean squared error (4.4%) to reference measurements, and at the height of 6.0 m, respective values are 6.5 mm (3.6%), +1.6 mm (0.9%) and 8.4 mm (4.8%). These values are smaller compared to most of the corresponding contemporary studies, and outperform the initial cylinder models. This indicates that the applied processing chain is capable of producing relatively accurate diameter measurements, which can, at the cost of computational heaviness, remove various defects and improve the modelling results. Numéro de notice : A2019-039 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.11.027 date de publication en ligne : 08/12/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.11.027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91976 [article]

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Structure from motion for ordered and unordered image sets based on random k-d forests and global pose estimation / Xin Wang in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 147 (January 2019) . - pp 19 - 41 Titre : Structure from motion for ordered and unordered image sets based on random k-d forests and global pose estimation Type de document : Article/Communication Auteurs : Xin Wang, Auteur ; Franz Rottensteiner, Auteur ; Christian Heipke, Auteur Année de publication : 2019 Article en page(s) : pp 19 - 41 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] chaîne de traitement [Termes descripteurs IGN] classification barycentrique [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] compensation par faisceaux [Termes descripteurs IGN] estimation de pose [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] matrice de rotation [Termes descripteurs IGN] orientation relative [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] recouvrement d'images [Termes descripteurs IGN] SIFT (algorithme) [Termes descripteurs IGN] structure-from-motion [Termes descripteurs IGN] vision par ordinateur Résumé : (auteur) In this paper, we present a new fast and robust method for structure from motion (SfM) for data sets potentially comprising thousands of ordered or unordered images. Our work focuses on the two most time-consuming procedures: (a) image matching and (b) pose estimation. For image matching, a new method employing a random k-d forest is proposed to quickly obtain pairs of overlapping images from an unordered set. After that, image matching and the estimation of relative orientation parameters are performed only for pairs found to be very likely to overlap. For pose estimation, we use a two-stage global approach, separating the determination of rotation matrices and translation parameters; the latter are computed simultaneously using a new method. In order to cope with outliers in the relative orientations, which global approaches are particularly sensitive to, we present a new constraint based on triplet loop closure errors of rotation and translation. Finally, a robust bundle adjustment is carried out to refine the image orientation parameters. We demonstrate the potential and limitations of our pipeline using various real-world datasets including ordered image data acquired from UAV (unmanned aerial vehicle) and other platforms as well as unordered data from the internet. The experiments show that our work performs better than comparable state-of-the-art SfM systems in terms of run time, while we achieve a similar accuracy and robustness. Numéro de notice : A2019-033 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.11.009 date de publication en ligne : 15/11/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.11.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91970 [article]

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Extraction of building roof planes with stratified random sample consensus / André C. Carrilho in Photogrammetric record, vol 33 n° 163 (September 2018)  

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Three-point-based solution for automated motion parameter estimation of a multi-camera indoor mapping system with planar motion constraint / Fangning He in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

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Machine learning and pose estimation for autonomous robot grasping with collaborative robots / Victor Talbot (2018) 

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Algebraic method to speed up robust algorithms: example of laser-scanned point clouds / B. Palancz in Survey review, vol 49 n° 357 (December 2017)  

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A Geometric and Radiometric Simultaneous Correction Model (GRSCM) framework for high-accuracy remotely sensed image preprocessing / Chang Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 9 (September 2017)  

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Mise en place d’un processus de dessin automatisé de plans d’intérieurs à partir de nuages de points acquis par LIDAR / Léa Talec (2017) 

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Automatic registration of MLS point clouds and SfM meshes of urban area / Reiji Yoshimura in Geo-spatial Information Science, vol 19 n° 3 (October 2016)  

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The reliability of RANSAC method when estimating the parameters of geometric object / Tilen Urbančič in Geodetski vestnik, vol 60 n° 1 (March - May 2016)  

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Construction de modèles 3D à partir de données vidéo fisheye / Julien Moreau (2016)  

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Conception d’une méthode de consolidation de grands réseaux lasergrammétriques / Emmanuel Cledat (2015) 

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