Centre dedocumentation
scientifique

Under-canopy UAV laser scanning for accurate forest field measurements / Eric Hyyppä in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 41 - 60 Titre : Under-canopy UAV laser scanning for accurate forest field measurements Type de document : Article/Communication Auteurs : Eric Hyyppä, Auteur ; Juha Hyyppä, Auteur ; Teemu Hakala, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 41 - 60 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] balayage laser [Termes descripteurs IGN] canopée [Termes descripteurs IGN] densité du bois [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] erreur moyenne quadratique [Termes descripteurs IGN] Finlande [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] hauteur à la base du houppier [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] inventaire forestier local [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] Simultaneous Localisation And Mapping [Termes descripteurs IGN] télédétection aérienne [Termes descripteurs IGN] télémètre laser terrestre [Termes descripteurs IGN] télémétrie laser aéroporté [Termes descripteurs IGN] tronc Résumé : (auteur) Surveying and robotic technologies are converging, offering great potential for robotic-assisted data collection and support for labour intensive surveying activities. From a forest monitoring perspective, there are several technological and operational aspects to address concerning under-canopy flying unmanned airborne vehicles (UAV). To demonstrate this emerging technology, we investigated tree detection and stem curve estimation using laser scanning data obtained with an under-canopy flying UAV. To this end, we mounted a Kaarta Stencil-1 laser scanner with an integrated simultaneous localization and mapping (SLAM) system on board an UAV that was manually piloted with the help of video goggles receiving a live video feed from the onboard camera of the UAV. Using the under-canopy flying UAV, we collected SLAM-corrected point cloud data in a boreal forest on two 32 m 32 m test sites that were characterized as sparse ( = 42 trees) and obstructed ( = 43 trees), respectively. Novel data processing algorithms were applied for the point clouds in order to detect the stems of individual trees and to extract their stem curves and diameters at breast height (DBH). The estimated tree attributes were compared against highly accurate field reference data that was acquired semi-manually with a multi-scan terrestrial laser scanner (TLS). The proposed method succeeded in detecting 93% of the stems in the sparse plot and 84% of the stems in the obstructed plot. In the sparse plot, the DBH and stem curve estimates had a root-mean-squared error (RMSE) of 0.60 cm (2.2%) and 1.2 cm (5.0%), respectively, whereas the corresponding values for the obstructed plot were 0.92 cm (3.1%) and 1.4 cm (5.2%). By combining the stem curves extracted from the under-canopy UAV laser scanning data with tree heights derived from above-canopy UAV laser scanning data, we computed stem volumes for the detected trees with a relative RMSE of 10.1% in both plots. Thus, the combination of under-canopy and above-canopy UAV laser scanning allowed us to extract the stem volumes with an accuracy comparable to the past best studies based on TLS in boreal forest conditions. Since the stems of several spruces located on the test sites suffered from severe occlusion and could not be detected with the stem-based method, we developed a separate work flow capable of detecting trees with occluded stems. The proposed work flow enabled us to detect 98% of trees in the sparse plot and 93% of the trees in the obstructed plot with a 100% correction level in both plots. A key benefit provided by the under-canopy UAV laser scanner is the short period of time required for data collection, currently demonstrated to be much faster than the time required for field measurements and TLS. The quality of the measurements acquired with the under-canopy flying UAV combined with the demonstrated efficiency indicates operational potential for supporting fast and accurate forest resource inventories. Numéro de notice : A2020-240 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.03.021 date de publication en ligne : 11/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.03.021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94994 [article]

Réservation

Réserver ce document

Exemplaires (3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2020061	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2020063	DEP-RECP	Revue	MATIS	Dépôt en unité	Exclu du prêt
081-2020062	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

A review of techniques for 3D reconstruction of indoor environments / Zhizhong Kang in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 5 (May 2020) . - 31 p. Titre : A review of techniques for 3D reconstruction of indoor environments Type de document : Article/Communication Auteurs : Zhizhong Kang, Auteur ; Juntao Yang, Auteur ; Zhou Yang, Auteur ; Sai Cheng, Auteur Année de publication : 2020 Article en page(s) : 31 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] espace intérieur [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] indoorGML [Termes descripteurs IGN] jeu de données localisées [Termes descripteurs IGN] modèle géométrique [Termes descripteurs IGN] modèle sémantique de données [Termes descripteurs IGN] modèle topologique de données [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] Simultaneous Localisation And Mapping Résumé : (auteur) Indoor environment model reconstruction has emerged as a significant and challenging task in terms of the provision of a semantically rich and geometrically accurate indoor model. Recently, there has been an increasing amount of research related to indoor environment reconstruction. Therefore, this paper reviews the state-of-the-art techniques for the three-dimensional (3D) reconstruction of indoor environments. First, some of the available benchmark datasets for 3D reconstruction of indoor environments are described and discussed. Then, data collection of 3D indoor spaces is briefly summarized. Furthermore, an overview of the geometric, semantic, and topological reconstruction of the indoor environment is presented, where the existing methodologies, advantages, and disadvantages of these three reconstruction types are analyzed and summarized. Finally, future research directions, including technique challenges and trends, are discussed for the purpose of promoting future research interest. It can be concluded that most of the existing indoor environment reconstruction methods are based on the strong Manhattan assumption, which may not be true in a real indoor environment, hence limiting the effectiveness and robustness of existing indoor environment reconstruction methods. Moreover, based on the hierarchical pyramid structures and the learnable parameters of deep-learning architectures, multi-task collaborative schemes to share parameters and to jointly optimize each other using redundant and complementary information from different perspectives show their potential for the 3D reconstruction of indoor environments. Furthermore, indoor–outdoor space seamless integration to achieve a full representation of both interior and exterior buildings is also heavily in demand. Numéro de notice : A2020-299 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9050330 date de publication en ligne : 19/05/2020 En ligne : https://doi.org/10.3390/ijgi9050330 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95139 [article]

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 descripteurs IGN] carte d'intérieur [Termes descripteurs IGN] carte de profondeur [Termes descripteurs IGN] cartographie 3D [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] état de l'art [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] intégration de données [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] séquence d'images [Termes descripteurs IGN] Simultaneous Localisation And Mapping [Termes descripteurs 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 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]

Réservation

Réserver ce document

Exemplaires (1)

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

Point clouds by SLAM-based mobile mapping systems: accuracy and geometric content validation in multisensor survey and stand-alone acquisition / Giulia Sammartano in Applied geomatics, vol 10 n° 4 (December 2018)  

Public [article]  inApplied geomatics > vol 10 n° 4 (December 2018) . - pp 317 - 339 Titre : Point clouds by SLAM-based mobile mapping systems: accuracy and geometric content validation in multisensor survey and stand-alone acquisition Type de document : Article/Communication Auteurs : Giulia Sammartano, Auteur ; Antonia Spanò, Auteur Année de publication : 2018 Article en page(s) : pp 317 - 339 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] carte d'intérieur [Termes descripteurs IGN] cartographie 3D [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] intégration de données [Termes descripteurs IGN] lever souterrain [Termes descripteurs IGN] modèle 3D du site [Termes descripteurs IGN] patrimoine culturel [Termes descripteurs IGN] patrimoine immobilier [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] Simultaneous Localisation And Mapping Résumé : (Auteur) The paper provides some operative replies to evaluate the effectiveness and the critical issues of the simultaneous localisation and mapping (SLAM)-based mobile mapping system (MMS) called ZEB by GeoSLAM™ https://geoslam.com/technology/. In these last years, this type of handheld 3D mapping technology has increasingly developed the framework of portable solutions for close-range mapping systems that have mainly been devoted to mapping the indoor building spaces of enclosed or underground environments, such as forestry applications and tunnels or mines. The research introduces a set of test datasets related to the documentation of landscape contexts or the 3D modelling of architectural complexes. These datasets are used to validate the accuracy and informative content richness about ZEB point clouds in stand-alone solutions and in cases of combined applications of this technology with multisensor survey approaches. In detail, the proposed validation method follows the fulfilment of the endorsed approach by use of root mean square error (RMSE) evaluation and deviation analysis assessment of point clouds between SLAM-based data and 3D point cloud surfaces computed by more precise measurement methods to evaluate the accuracy of the proposed approach. Furthermore, this study specifies the suitable scale for possible handlings about these peculiar point clouds and uses the profile extraction method in addition to feature analyses such as corner and plane deviation analysis of architectural elements. Finally, because of the experiences reported in the literature and performed in this work, a possible reversal is suggested. If in the 2000s, most studies focused on intelligently reducing the light detection and ranging (LiDAR) point clouds where they presented redundant and not useful information, contrariwise, in this sense, the use of MMS methods is proposed to be firstly considered and then to increase the information only wherever needed with more accurate high-scale methods. Numéro de notice : A2018-590 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-018-0221-7 date de publication en ligne : 01/06/2018 En ligne : https://doi.org/10.1007/s12518-018-0221-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92514 [article]

Image-LASER fusion for 3D modelling in complex environments / Daniela Craciun (2010)

Public Titre : Image-LASER fusion for 3D modelling in complex environments Type de document : Thèse/HDR Auteurs : Daniela Craciun, Auteur ; Nicolas Paparoditis , Directeur de thèse Editeur : Paris [France] : Télécom ParisTech Année de publication : 2010 Importance : 286 p. Format : 21 x 30 cm Note générale : bibliographie Thèse présentée pour obtenir le grade de Docteur Télécom ParisTech, Spécialité Signal et Images Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] automatisation [Termes descripteurs IGN] chaîne de traitement [Termes descripteurs IGN] données laser [Termes descripteurs IGN] fusion d'images [Termes descripteurs IGN] image gigapixel [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] mosaïquage d'images [Termes descripteurs IGN] Simultaneous Localisation And Mapping Résumé : (auteur) One might wonder what can be gained from the image-laser fusion and in which measure such a hybrid system can generate automatically complete and photorealist 3D models of difficult to access and unstructured underground environments. In such environments, special attention must be given to the main issue standing behind the automation of the 3D modeling pipeline whic is represented by the capacity to match reliably image and laser data in GPS-denied and feature-less areas. In addition, time and in-situ access constraints require fast and automatic procedures for in-situ data acquisition, processing and interpretation in order to allow for in situ verification of the 3D scene model completeness. Finally, the currently generated 3D model represents the only available information providing situational awareness based on which autonomous behavior must be build in order to enable the system to act intelligently onthe- fly and explore the environment for ensuring the 3D scene model completeness. This dissertation evaluates the potential of a hybrid image-laser system for generating in-situ complete and photorealist 3D models of challenging environments, without requiring human operator intervention. The presented research focuses on two main aspects: (i) the automation of the 30 modeling pipeline, targeting the automatic data matching in feature-less and GPS-denied areas for in situ world modeling and (ii) the exploitation of the generated 3D models along with visual servoing procedures to provide mobile systems with autonomous site digitization and exploration capabilities. We design a complementary and cooperative image-laser fusion which lead to a 4D mosaicing sensor prototype. Note de contenu : 1- Introduction and motivation 2- Why and how to perform in-situ 3D modelling ? 3- ARTVISYS: ARTificial VIsion-based SYStem 4- Multi-view scans alignment for in-situ 3D mocaicing 5- AGM: Automatic gigapixel mocaicing for nodal optical images 6- Generating 4D dual mosaics from image and laser data 7- Toward 4D panoramic-driven siteexploration Conclusion and research perspectives Numéro de notice : 25501 Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de doctorat : Signal et Imagerie : Paris : 2010 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94350

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
25501-01	K321	Livre	Saint-Mandé	Dépôt en unité	Exclu du prêt

Scan matching in polar coordinates with application to SLAM / Albert Diosi (2005)

Permalink