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Efficient terrestrial laser scan segmentation exploiting data structure / Hamid Mahmoudabadi in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
[article]
Titre : Efficient terrestrial laser scan segmentation exploiting data structure Type de document : Article/Communication Auteurs : Hamid Mahmoudabadi, Auteur ; Michael J. Olsen, Auteur ; Sinisa Todorovic, Auteur Année de publication : 2016 Article en page(s) : pp 135 - 150 Note générale : Bibliogaphie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] colorimétrie
[Termes IGN] densité d'information
[Termes IGN] intensité lumineuse
[Termes IGN] modèle logique de données
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] système de coordonnées
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) New technologies such as lidar enable the rapid collection of massive datasets to model a 3D scene as a point cloud. However, while hardware technology continues to advance, processing 3D point clouds into informative models remains complex and time consuming. A common approach to increase processing efficiently is to segment the point cloud into smaller sections. This paper proposes a novel approach for point cloud segmentation using computer vision algorithms to analyze panoramic representations of individual laser scans. These panoramas can be quickly created using an inherent neighborhood structure that is established during the scanning process, which scans at fixed angular increments in a cylindrical or spherical coordinate system. In the proposed approach, a selected image segmentation algorithm is applied on several input layers exploiting this angular structure including laser intensity, range, normal vectors, and color information. These segments are then mapped back to the 3D point cloud so that modeling can be completed more efficiently. This approach does not depend on pre-defined mathematical models and consequently setting parameters for them. Unlike common geometrical point cloud segmentation methods, the proposed method employs the colorimetric and intensity data as another source of information. The proposed algorithm is demonstrated on several datasets encompassing variety of scenes and objects. Results show a very high perceptual (visual) level of segmentation and thereby the feasibility of the proposed algorithm. The proposed method is also more efficient compared to Random Sample Consensus (RANSAC), which is a common approach for point cloud segmentation. Numéro de notice : A2016-781 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.05.015 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.05.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82477
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 135 - 150[article]Measures of transport mode segmentation of trajectories / Adrain C. Prelipcean in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
[article]
Titre : Measures of transport mode segmentation of trajectories Type de document : Article/Communication Auteurs : Adrain C. Prelipcean, Auteur ; Gyözö Gidofalvi, Auteur ; Yusak O. Susilo, Auteur Année de publication : 2016 Article en page(s) : pp 1763 - 1805 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse diachronique
[Termes IGN] analyse spatio-temporelle
[Termes IGN] calcul d'erreur
[Termes IGN] itinéraire
[Termes IGN] navigation
[Termes IGN] segmentation
[Termes IGN] transportRésumé : (Auteur) Rooted in the philosophy of point- and segment-based approaches for transportation mode segmentation of trajectories, the measures that researchers have adopted to evaluate the quality of the results (1) are incomparable across approaches, hence slowing the progress in the field and (2) do not provide insight about the quality of the continuous transportation mode segmentation. To address these problems, this paper proposes new error measures that can be applied to measure how well a continuous transportation mode segmentation model performs. The error measures introduced are based on aligning multiple inferred continuous intervals to ground truth intervals, and measure the cardinality of the alignment and the spatial and temporal discrepancy between the corresponding aligned segments. The utility of this new way of computing errors is shown by evaluating the segmentation of three generic transportation mode segmentation approaches (implicit, explicit–holistic, and explicit–consensus-based transport mode segmentation), which can be implemented in a thick client architecture. Empirical evaluations on a large real-word data set reveal the superiority of explicit–consensus-based transport mode segmentation, which can be attributed to the explicit modeling of segments and transitions, which allows for a meaningful decomposition of the complex learning task. Numéro de notice : A2016-568 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1137297 Date de publication en ligne : 29/01/2016 En ligne : http://dx.doi.org/10.1080/13658816.2015.1137297 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81712
in International journal of geographical information science IJGIS > vol 30 n° 9-10 (September - October 2016) . - pp 1763 - 1805[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Automatic extraction of road networks from GPS traces / Jia Qiu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 8 (August 2016)
[article]
Titre : Automatic extraction of road networks from GPS traces Type de document : Article/Communication Auteurs : Jia Qiu, Auteur ; Ruisheng Wang, Auteur Année de publication : 2016 Article en page(s) : pp 593 - 604 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] analyse de groupement
[Termes IGN] appariement de points
[Termes IGN] compensation par moindres carrés
[Termes IGN] données GPS
[Termes IGN] extraction automatique
[Termes IGN] extraction de données
[Termes IGN] modèle de Markov
[Termes IGN] relation topologique
[Termes IGN] réseau routier
[Termes IGN] segmentationRésumé : (auteur) We propose a point segmentation and grouping method to generate road maps from GPS traces. First, we present a progressive point cloud segmentation algorithm based on Total Least Squares (TLS) line fitting. Second, we group topologically connected point clusters by the point's orientation and cluster's spatial proximity, where the topological relationship is generated using Hidden Markov Model (HMM) map matching. Finally, we refine the intersections of roads so that their geometrical and topological relationships are consistent with each other. Experimental results show that our algorithm is robust to noises and the generated road network has a high accuracy in terms of geometry and topology. Compare to the representative algorithms; the results of our new algorithm have a higher F-measure score for different matching thresholds. Numéro de notice : A2016-606 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE/POSITIONNEMENT Nature : Article DOI : 10.14358/PERS.82.8.593 En ligne : http://dx.doi.org/10.14358/PERS.82.8.593 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81796
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 8 (August 2016) . - pp 593 - 604[article]From Aristotle to semantic analysis / Allan Gajadhar in Research information, n° 85 (August - September 2016)
[article]
Titre : From Aristotle to semantic analysis Type de document : Article/Communication Auteurs : Allan Gajadhar, Auteur Année de publication : 2016 Article en page(s) : pp 10 - 11 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Documentation
[Termes IGN] ontologie
[Termes IGN] segmentation sémantiqueRésumé : (éditeur) The need to organise information efficiently and reliably is more important than ever, argues the author. Numéro de notice : A2016-477 Affiliation des auteurs : non IGN Thématique : SOCIETE NUMERIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81491
in Research information > n° 85 (August - September 2016) . - pp 10 - 11[article]Documents numériques
en open access
A2016-477_From Aristotle to semantic analysisAdobe Acrobat PDF A novel computer-aided tree species identification method based on burst wind segmentation of 3D bark textures / Alice Ahlem Othmani in Machine Vision and Applications, vol 27 n° 5 (July 2016)
[article]
Titre : A novel computer-aided tree species identification method based on burst wind segmentation of 3D bark textures Type de document : Article/Communication Auteurs : Alice Ahlem Othmani, Auteur ; Cansen Jiang, Auteur ; Nicolas Lomenie, Auteur ; Jean-Marie Favreau, Auteur ; Alexandre Piboule, Auteur ; Lew F. C. Lew Yan Voon, Auteur Année de publication : 2016 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse comparative
[Termes IGN] arbre (flore)
[Termes IGN] classification
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] écorce
[Termes IGN] extraction d'arbres
[Termes IGN] forêt tempérée
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] reconnaissance de formes
[Termes IGN] segmentation
[Termes IGN] texture d'image
[Termes IGN] zone saillante 3DRésumé : (auteur) Terrestrial Laser Scanning (TLS) systems have gained increasing popularity in the forestry domain and are today widely used for the automatic measurement of forest inventory attributes. Nevertheless, to the best of our knowledge the problem of tree species recognition from TLS data has received very little attention from the scientific community. It is in this context that we present a novel Computer-Aided Tree Species Identification method based on 3D bark texture analysis. The novelty of our approach resides in the following three key points: (1) 3D salient regions extraction using a new morphological segmentation method that we have called Burst Wind Segmentation, (2) the extraction and pre-annotation of a collection of typical 3D bark patterns, known as scars, from each of the tree species. The pre-annotated scars are stored in a dictionary that we have called ScarBook and they are used as a reference for the comparison of the 3D salient segmented regions, (3) a wide variety of advanced shape, saliency, curvature and roughness features are extracted from the 3D salient segmented regions. To study the performance of our method, an experiment has been carried out on a dataset composed of 969 patches which correspond to 30 cm long segments of the trunk at breast height. Six species among the most dominant species in European forests have been tested with patches of different diameter at breast height values so as to study the identification accuracy with respect to age. The results obtained are very encouraging and promising and they confirm the possibility of identifying tree species using TLS data. Numéro de notice : A2016--134 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s00138-015-0738-2 Date de publication en ligne : 28/11/2015 En ligne : https://doi.org/10.1007/s00138-015-0738-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85267
in Machine Vision and Applications > vol 27 n° 5 (July 2016)[article]A multi-scale plane-detection method based on the Hough transform and region growing / Xiaoxu Leng in Photogrammetric record, vol 31 n° 154 (June - August 2016)PermalinkPrivacy and spatial pattern preservation in masked GPS trajectory data / Dara E. Seidl in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)PermalinkSpatial optimization for regionalization problems with spatial interaction: a heuristic approach / Kamyoung Kim in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)PermalinkObject classification and recognition from mobile laser scanning point clouds in a road environment / Matti Lehtomäki in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)PermalinkPermalinkPermalinkPermalinkDetection, segmentation and localization of individual trees from MMS point cloud data / Martin Weinmann (2016)PermalinkRemote Sensing Observations of Continental Surfaces, ch. 6. Airborne lidar data processing / Clément Mallet (2016)PermalinkSegmentation and localization of individual trees from MMS point cloud data acquired in urban areas / Martin Weinmann (2016)Permalink