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Improving traffic sign recognition results in urban areas by overcoming the impact of scale and rotation / R. Yazdan in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 171 (January 2021) . - pp 18 - 35 Titre : Improving traffic sign recognition results in urban areas by overcoming the impact of scale and rotation Type de document : Article/Communication Auteurs : R. Yazdan, Auteur ; M. Varshosaz, Auteur Année de publication : 2021 Article en page(s) : pp 18 - 35 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] base de données d'images [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] corrélation à l'aide de traits caractéristiques [Termes descripteurs IGN] corrélation croisée normalisée [Termes descripteurs IGN] couple stéréoscopique [Termes descripteurs IGN] détection automatique [Termes descripteurs IGN] modèle stéréoscopique [Termes descripteurs IGN] reconnaissance d'objets [Termes descripteurs IGN] segmentation d'image [Termes descripteurs IGN] SIFT (algorithme) [Termes descripteurs IGN] signalisation routière [Termes descripteurs IGN] SURF (algorithme) [Termes descripteurs IGN] Téhéran [Termes descripteurs IGN] transformation de Hough [Termes descripteurs IGN] zone urbaine Résumé : (auteur) Automatic detection and recognition of traffic signs have many applications. However, some problems can affect the accuracy of the existing algorithms, such as changes in environmental light conditions, shadows, the presence of objects of the same colour, significant changes in scale and rotation, as well as obstacles in front of the traffic signs. To overcome these difficulties, a reference image database is usually used that includes different modes of appearing the traffic signs in the images. In order to overcome the effects of scale and rotation, in this paper a new method is presented in which only one reference image is needed for each sign to recognise the traffic sign in an image. In the proposed method, imaging is done in stereo. Using the captured image pair, a virtual image is generated which is then used to recognise the sign. As a result, the recognition is carried out with a minimum number of reference images. Experiments show that the proposed algorithm significantly improves recognition results. The traffic signs are recognised with 93.1% accuracy that enjoys a 4.9% improvement over traditional methods. Numéro de notice : A2021-010 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.003 date de publication en ligne : 06/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.003 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96304 [article]

Stereophotogrammetry for 2-D building deformation monitoring using Kalman Filter / J.O. Odumosu in Reports on geodesy and geoinformatics, vol 110 n°1 (December 2020)  

Public [article]  inReports on geodesy and geoinformatics > vol 110 n°1 (December 2020) . - pp 1 - 7 Titre : Stereophotogrammetry for 2-D building deformation monitoring using Kalman Filter Type de document : Article/Communication Auteurs : J.O. Odumosu, Auteur ; V.C. Nnam, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1 - 7 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie terrestre [Termes descripteurs IGN] corrélation croisée normalisée [Termes descripteurs IGN] déformation d'édifice [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] Matlab [Termes descripteurs IGN] modèle stéréoscopique [Termes descripteurs IGN] Nigéria [Termes descripteurs IGN] point d'appui [Termes descripteurs IGN] surveillance d'ouvrage [Termes descripteurs IGN] télémètre laser terrestre [Termes descripteurs IGN] transformation polynomiale Résumé : (auteur) Stereo photogrammetry has been used in this study to analyse and detect movements within the Lecture theater of School of Environmental Technology of Federal University of Technology Minna via the use of Kalman filter algorithm. The essential steps for implementation of this method are herein highlighted and results obtained indicate Ins. Mov.s (velocity) ranging from ±0.0000001 m/epoch to ±0.000007 m/epoch with greater movements noticed in the horizontal direction than in the vertical direction of the building. Because the observed movements were insignificant, the building has been classified as stable. However, a longer period of observation with a bi-monthly observational interval has been recommended to enable decision on the rate of rise/sink and deformation of the building. Numéro de notice : A2020-785 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.2478/rgg-2020-0006 date de publication en ligne : 07/08/2020 En ligne : https://doi.org/10.2478/rgg-2020-0006 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96530 [article]

Application of 30-meter global digital elevation models for compensating rational polynomial coefficients biases / Amin Alizadeh Naeini in Geocarto international, vol 35 n° 12 ([01/09/2020])  

Public [article]  inGeocarto international > vol 35 n° 12 [01/09/2020] . - pp 1311 - 1326 Titre : Application of 30-meter global digital elevation models for compensating rational polynomial coefficients biases Type de document : Article/Communication Auteurs : Amin Alizadeh Naeini, Auteur ; Sayyed Bagher Fatemi, Auteur ; Masoud Babadi, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1311 - 1326 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] correction d'image [Termes descripteurs IGN] image Cartosat-1 [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] MNS ASTER [Termes descripteurs IGN] MNS SRTM [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] modèle par fonctions rationnelles [Termes descripteurs IGN] modèle stéréoscopique [Termes descripteurs IGN] point d'appui [Termes descripteurs IGN] précision géométrique (imagerie) Résumé : (auteur) Generation of precise digital elevation models (DEMs) from stereo satellite images by using rational polynomial coefficients (RPCs) usually needs several ground control points (GCPs). This is mainly due to RPCs biases. However, since GCPs collection is a time consuming and expensive process, global DEMs (GDEMs), as the most inexpensive geospatial information, can be used to improve stereo satellite imagery-based DEMs (IB-DEMs). In this study, a 2.5 D mutual information based DEM matching, between a GDEM and an IB-DEM, was introduced for bias correction of satellite stereo images. Three well-known 30-meter GDEMs, namely, SRTM, ASTER, and AW3D30, were used and compared to assess the efficiency of this approach. The performance of the proposed method was evaluated by processing the stereo images acquired by CARTOSAT-1 satellite from two regions with flat, hilly, and mountainous topography. Evaluation results revealed that the proposed method could significantly improve the geometric accuracy of IB-DEM using all GDEMs. Numéro de notice : A2020-481 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1573854 date de publication en ligne : 01/03/2019 En ligne : https://doi.org/10.1080/10106049.2019.1573854 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95632 [article]

Post‐filtering with surface orientation constraints for stereo dense image matching / Xu Huang in Photogrammetric record, vol 35 n° 171 (September 2020)  

Public [article]  inPhotogrammetric record > vol 35 n° 171 (September 2020) . - pp 375-401 Titre : Post‐filtering with surface orientation constraints for stereo dense image matching Type de document : Article/Communication Auteurs : Xu Huang, Auteur ; Rongjun Qin, Auteur Année de publication : 2020 Article en page(s) : pp 375-401 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] corrélation automatique de points homologues [Termes descripteurs IGN] corrélation d'images [Termes descripteurs IGN] filtrage numérique d'image [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] modèle stéréoscopique [Termes descripteurs IGN] orientation d'image Résumé : (Auteur) Dense image matching (DIM) is a critical technique when computing accurate 3D geometric information for many photogrammetric applications. Most DIM methods adopt first‐order regularisation priors for efficient matching, which often introduce stepped biases (also called fronto‐parallel biases) into the matching results. To remove these biases and compute more accurate matching results, this paper proposes a novel post‐filtering method by adjusting the surface orientation of each pixel in the matching process. The core algorithm formulates the post‐filtering as the optimisation of a global energy function with second‐order regularisation priors. A compromise solution of the energy function is computed by breaking the optimisation into a collection of sub‐optimisations of each pixel in a local adaptive window. The proposed method was compared with several state‐of‐the‐art post‐filtering methods on indoor, aerial and satellite datasets. The comparisons demonstrate that the proposed method obtains the highest post‐filtering accuracies on all datasets. Numéro de notice : A2020-437 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12333 date de publication en ligne : 20/09/2020 En ligne : https://doi.org/10.1111/phor.12333 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95843 [article]

Vehicle detection of multi-source remote sensing data using active fine-tuning network / Xin Wu in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 167 (September 2020) . - pp 39 - 53 Titre : Vehicle detection of multi-source remote sensing data using active fine-tuning network Type de document : Article/Communication Auteurs : Xin Wu, Auteur ; Wei Li, Auteur ; Danfeng Hong, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 39 - 53 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] Allemagne [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] détection d'objet [Termes descripteurs IGN] données multisources [Termes descripteurs IGN] étiquette [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] modèle stéréoscopique [Termes descripteurs IGN] segmentation [Termes descripteurs IGN] segmentation sémantique [Termes descripteurs IGN] véhicule Résumé : (auteur) Vehicle detection in remote sensing images has attracted increasing interest in recent years. However, its detection ability is limited due to lack of well-annotated samples, especially in densely crowded scenes. Furthermore, since a list of remotely sensed data sources is available, efficient exploitation of useful information from multi-source data for better vehicle detection is challenging. To solve the above issues, a multi-source active fine-tuning vehicle detection (Ms-AFt) framework is proposed, which integrates transfer learning, segmentation, and active classification into a unified framework for auto-labeling and detection. The proposed Ms-AFt employs a fine-tuning network to firstly generate a vehicle training set from an unlabeled dataset. To cope with the diversity of vehicle categories, a multi-source based segmentation branch is then designed to construct additional candidate object sets. The separation of high quality vehicles is realized by a designed attentive classifications network. Finally, all three branches are combined to achieve vehicle detection. Extensive experimental results conducted on two open ISPRS benchmark datasets, namely the Vaihingen village and Potsdam city datasets, demonstrate the superiority and effectiveness of the proposed Ms-AFt for vehicle detection. In addition, the generalization ability of Ms-AFt in dense remote sensing scenes is further verified on stereo aerial imagery of a large camping site. Numéro de notice : A2020-546 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.06.016 date de publication en ligne : 13/07/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.06.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95772 [article]

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