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Georeferenced measurements of building objects with their simultaneous shape detection / Edward Osada in Survey review, Vol 52 n°370 (Janvier 2020)  

Public [article]  inSurvey review > Vol 52 n°370 (Janvier 2020) . - pp 24 - 30 Titre : Georeferenced measurements of building objects with their simultaneous shape detection Type de document : Article/Communication Auteurs : Edward Osada, Auteur ; Krzysztof Karsznia, Auteur ; Izabela Karsznia, Auteur Année de publication : 2020 Article en page(s) : pp 24 - 30 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Topographie [Termes descripteurs IGN] ajustement de paramètres [Termes descripteurs IGN] bâtiment [Termes descripteurs IGN] compensation par moindres carrés [Termes descripteurs IGN] détection de contours [Termes descripteurs IGN] information géographique [Termes descripteurs IGN] mesurage d'angles [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] point de nivellement [Termes descripteurs IGN] point GNSS nivelé [Termes descripteurs IGN] reconnaissance de formes Résumé : (auteur) The paper presents a new method of georeferenced measurements of building objects with their simultaneous shape detection. The method is based on a robust adjustment of a linear network localised on the measured object and connected to GNSS-surveyed points deployed near building corners. In the robust adjustment process, the angles of the object physically outlying from their theoretical design values are detected, the remaining angles retain the design values. The performed field surveying experiment underlined the effectiveness of the proposed method. Numéro de notice : A2020-025 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1511033 date de publication en ligne : 17/08/2018 En ligne : https://doi.org/10.1080/00396265.2018.1511033 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94473 [article]

Robust pose estimation and calibration of catadioptric cameras with spherical mirrors / Sagi Filin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 1 (January 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 1 (January 2020) . - pp 33 - 44 Titre : Robust pose estimation and calibration of catadioptric cameras with spherical mirrors Type de document : Article/Communication Auteurs : Sagi Filin, Auteur ; Grigory Ilizirov, Auteur ; Bashar Elnashef, Auteur Année de publication : 2020 Article en page(s) : pp 33 - 44 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes descripteurs IGN] estimation de pose [Termes descripteurs IGN] étalonnage de chambre métrique [Termes descripteurs IGN] flux lumineux [Termes descripteurs IGN] lentille [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] miroir [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] sphère [Termes descripteurs IGN] trilatération Résumé : (Auteur) Catadioptric cameras broaden the field of view and reveal otherwise occluded object parts. They differ geometrically from central-perspective cameras because of light reflection from the mirror surface. To handle these effects, we present new pose-estimation and reconstruction models for imaging through spherical mirrors. We derive a closed-form equivalent to the collinearity principle via which three methods are established to estimate the system parameters: a resection-based one, a trilateration-based one that introduces novel constraints that enhance accuracy, and a direct and linear transform-based one. The estimated system parameters exhibit improved accuracy compared to the state of the art, and analysis shows intrinsic robustness to the presence of a high fraction of outliers. We then show that 3D point reconstruction can be performed at accurate levels. Thus, we provide an in-depth look into the geometrical modeling of spherical catadioptric systems and practical enhancements of accuracies and requirements to reach them. Numéro de notice : A2020-050 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.1.33 date de publication en ligne : 01/01/2020 En ligne : https://doi.org/10.14358/PERS.86.1.33 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94535 [article]

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Robust acquisition at GPS receivers in unsafe locations using complex wavelet transform / M. Moazedi in Survey review, vol 51 n° 369 (November 2019)  

Public [article]  inSurvey review > vol 51 n° 369 (November 2019) . - pp 514 - 524 Titre : Robust acquisition at GPS receivers in unsafe locations using complex wavelet transform Type de document : Article/Communication Auteurs : M. Moazedi, Auteur ; Mohammad-Reza Mosavi, Auteur ; A. Sadr, Auteur Année de publication : 2019 Article en page(s) : pp 514 - 524 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] anti-leurrage [Termes descripteurs IGN] interférence [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] récepteur GPS [Termes descripteurs IGN] signal GPS [Termes descripteurs IGN] transformation en ondelettes Résumé : (auteur) Growing importance of Global Positioning System (GPS) applications in various fields, leads many researches to the security of GPS systems and investigation of eventual perturbations in them. One of the most important intentional interferences is spoofing. This work presents an anti-spoofing method based on complex wavelet transform (CWT). Fake satellites are omitted and then understrength satellites due to spoofing are identified. The results of investigation suggest that the proposed CWT based estimation and extraction method is better than relatively simple wavelet transform. The suggested filter is applied in the Intermediate Frequency signal. Cross-validation technique is used for automatically identifying wavelet signal layers. The proposed method has been implemented on different collected datasets. Software GPS Receiver has been used to implement and validate the developed anti-spoofing technique because it is more flexible and economical compared with usual hardware receivers. Numéro de notice : A2019-573 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1483597 date de publication en ligne : 18/06/2018 En ligne : https://doi.org/10.1080/00396265.2018.1483597 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94449 [article]

Learning and adapting robust features for satellite image segmentation on heterogeneous data sets / Sina Ghassemi in IEEE Transactions on geoscience and remote sensing, vol 57 n° 9 (September 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 9 (September 2019) . - pp 6517 - 6529 Titre : Learning and adapting robust features for satellite image segmentation on heterogeneous data sets Type de document : Article/Communication Auteurs : Sina Ghassemi, Auteur ; Attilio Friandrotti, Auteur ; Gianluca Francini, Auteur ; Enrico Magli, Auteur Année de publication : 2019 Article en page(s) : pp 6517 - 6529 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] chaîne de traitement [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] coût [Termes descripteurs IGN] données hétérogènes [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] réseau neuronal convolutif [Termes descripteurs IGN] segmentation d'image [Termes descripteurs IGN] test de performance Résumé : (auteur) This paper addresses the problem of training a deep neural network for satellite image segmentation so that it can be deployed over images whose statistics differ from those used for training. For example, in postdisaster damage assessment, the tight time constraints make it impractical to train a network from scratch for each image to be segmented. We propose a convolutional encoder–decoder network able to learn visual representations of increasing semantic level as its depth increases, allowing it to generalize over a wider range of satellite images. Then, we propose two additional methods to improve the network performance over each specific image to be segmented. First, we observe that updating the batch normalization layers’ statistics over the target image improves the network performance without human intervention. Second, we show that refining a trained network over a few samples of the image boosts the network performance with minimal human intervention. We evaluate our architecture over three data sets of satellite images, showing the state-of-the-art performance in binary segmentation of previously unseen images and competitive performance with respect to more complex techniques in a multiclass segmentation task. Numéro de notice : A2019-341 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2906689 date de publication en ligne : 17/04/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2906689 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93379 [article]

Spatially-explicit sensitivity and uncertainty analysis in a MCDA-based flood vulnerability model / Mariana Madruga de bruto in International journal of geographical information science IJGIS, vol 33 n° 9 (September 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 33 n° 9 (September 2019) . - pp 1788-1806 Titre : Spatially-explicit sensitivity and uncertainty analysis in a MCDA-based flood vulnerability model Type de document : Article/Communication Auteurs : Mariana Madruga de bruto, Auteur ; Adrian Almoradie, Auteur ; Mariele Evers, Auteur Année de publication : 2019 Article en page(s) : pp 1788-1806 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse de sensibilité [Termes descripteurs IGN] analyse multicritère [Termes descripteurs IGN] Brésil [Termes descripteurs IGN] Geospatial data abstraction library [Termes descripteurs IGN] incertitude des données [Termes descripteurs IGN] inondation [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] processus d'analyse hiérarchisée [Termes descripteurs IGN] Python (langage de programmation) [Termes descripteurs IGN] vulnérabilité [Termes descripteurs IGN] zone à risque Résumé : (auteur) This study presents a methodology for conducting sensitivity and uncertainty analysis of a GIS-based multi-criteria model used to assess flood vulnerability in a case study in Brazil. The paper explores the robustness of model outcomes against slight changes in criteria weights. One criterion was varied at-a-time, while others were fixed to their baseline values. An algorithm was developed using Python and a geospatial data abstraction library to automate the variation of weights, implement the ANP (analytic network process) tool, reclassify the raster results, compute the class switches, and generate an uncertainty surface. Results helped to identify highly vulnerable areas that are burdened by high uncertainty and to investigate which criteria contribute to this uncertainty. Overall, the criteria ‘houses with improper building material’ and ‘evacuation drills and training’ are the most sensitive ones, thus, requiring more accurate measurements. The sensitivity of these criteria is explained by their weights in the base run, their spatial distribution, and the spatial resolution. These findings can support decision makers to characterize, report, and mitigate uncertainty in vulnerability assessment. The case study results demonstrate that the developed approach is simple, flexible, transparent, and may be applied to other complex spatial problems. Numéro de notice : A2019-389 Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1599125 date de publication en ligne : 05/04/2019 En ligne : https://doi.org/10.1080/13658816.2019.1599125 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93480 [article]

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Robust M–M unscented Kalman filtering for GPS/IMU navigation / Cheng Yang in Journal of geodesy, vol 93 n° 8 (August 2019)  

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Demonstrating the transferability of forest inventory attribute models derived using airborne laser scanning data / Piotr Tompalski in Remote sensing of environment, vol 227 (15 June 2019)  

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A breakpoint detection in the mean model with heterogeneous variance on fixed time-intervals / Olivier Bock in Statistics and Computing, vol 29 Online First (May 2019)  

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Coastline extraction from SAR images using robust ridge tracing / Dailiang Wang in Marine geodesy, vol 42 n° 3 (May 2019)  

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A derivative-free optimization-based approach for detecting architectural symmetries from 3D point clouds / Fan Xue in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)  

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Robust vehicle detection in aerial images using bag-of-words and orientation aware scanning / Hailing Zhou in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)  

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Adaptive correlation filters with long-term and short-term memory for object tracking / Chao Ma in International journal of computer vision, vol 126 n° 8 (August 2018)  

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A deep neural network with spatial pooling (DNNSP) for 3-D point cloud classification / Zhen Wang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 8 (August 2018)  

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Robust detection and affine rectification of planar homogeneous texture for scene understanding / Shahzor Ahmad in International journal of computer vision, vol 126 n° 8 (August 2018)  

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Label propagation with ensemble of pairwise geometric relations : towards robust large-scale retrieval of object instances / Xiaomeng Wu in International journal of computer vision, vol 126 n° 7 (July 2018)  

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