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Visibility monitoring using conventional roadside cameras : Emerging applications / Raouf Babari in Transportation Research - Part C: Emerging Technologies, vol 22 (June 2012)
[article]
Titre : Visibility monitoring using conventional roadside cameras : Emerging applications Type de document : Article/Communication Auteurs : Raouf Babari, Auteur ; Nicolas Hautière, Auteur ; Eric Dumont, Auteur ; Nicolas Paparoditis , Auteur ; James Misener, Auteur Année de publication : 2012 Article en page(s) : pp 17 - 28 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] autoroute
[Termes IGN] caméra numérique
[Termes IGN] données météorologiques
[Termes IGN] qualité de l'air
[Termes IGN] régression non linéaire
[Termes IGN] sécurité routière
[Termes IGN] visibilité (optique)Résumé : (auteur) The measurement of atmospheric visibility is an important element for road and air transportation safety. We propose in this paper a novel estimator of the atmospheric visibility by already existing conventional highway cameras, with a technique based on the gradient magnitude selected by applying Lambert’s law with respect to changes in lighting conditions. The response of this estimator is calibrated by non-linear regression with data from a visibility meter installed in a test site which has been instrumented with a camera. Through our technique, atmospheric visibility estimates are obtained with an average error of 30% for images taken in the day, with sky luminance between 10 and 8000 cd m−2 and visibility distances up to 15 km. Our results allow us to envision practical implementation on roadsides in the near future to determine local visibility for the benefit of road safety, meteorological observation and air quality monitoring. Numéro de notice : A2012-744 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.trc.2011.11.012 Date de publication en ligne : 29/11/2011 En ligne : https://doi.org/10.1016/j.trc.2011.11.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91508
in Transportation Research - Part C: Emerging Technologies > vol 22 (June 2012) . - pp 17 - 28[article]A model-driven approach to estimate atmospheric visibility with ordinary cameras / Raouf Babari in Atmospheric Environment, vol 45 n° 30 (September 2011)
[article]
Titre : A model-driven approach to estimate atmospheric visibility with ordinary cameras Type de document : Article/Communication Auteurs : Raouf Babari, Auteur ; Nicolas Hautière, Auteur ; Eric Dumont, Auteur ; Roland Brémond, Auteur ; Nicolas Paparoditis , Auteur Année de publication : 2011 Article en page(s) : pp 5316 - 5324 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] caméra numérique
[Termes IGN] éclairement lumineux
[Termes IGN] qualité de l'air
[Termes IGN] scène
[Termes IGN] sécurité routière
[Termes IGN] visibilité (optique)Résumé : (Auteur) Atmospheric visibility is an important input for road and air transportation safety, as well as a good proxy to estimate the air quality. A model-driven approach is presented to monitor the meteorological visibility distance through use of ordinary outdoor cameras. Unlike in previous data-driven approaches, a physics-based model is proposed which describes the mapping function between the contrast distribution in the image and the atmospheric visibility. The model is non-linear, which allows encompassing a large spectrum of applications. The model assumes a continuous distribution of objects with respect to the distance in the scene and is estimated by a novel process. It is more robust to illumination variations by selecting the Lambertian surfaces in the scene. To evaluate the relevance of the approach, a publicly available database is used. When the model is fitted to short range data, the proposed method is shown to be effective and to improve on existing methods. In particular, it allows envisioning an easier deployment of these camera-based techniques on multiple observation sites. Numéro de notice : A2011-596 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.atmosenv.2011.06.053 Date de publication en ligne : 28/06/2011 En ligne : https://doi.org/10.1016/j.atmosenv.2011.06.053 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91528
in Atmospheric Environment > vol 45 n° 30 (September 2011) . - pp 5316 - 5324[article]
Titre : Computer vision for the remote sensing of atmospheric visibility Type de document : Article/Communication Auteurs : Raouf Babari, Auteur ; Nicolas Hautière, Auteur ; Eric Dumont, Auteur ; Jean-Pierre Papelard , Auteur ; Nicolas Paparoditis , Auteur Editeur : New-York : IEEE Computer society Année de publication : 2011 Conférence : ICCVW 2011, IEEE International Conference on Computer Vision Workshops 06/11/2011 13/11/2011 Barcelone Espagne Proceedings IEEE Importance : pp Note générale : bibliographie Langues : Anglais (eng) Résumé : (auteur) Atmospheric visibility distance is a property of the atmosphere, which can be remotely sensed by computer vision. In this aim, a non-linear mapping function between the atmospheric visibility distance and the contrast in images must be estimated. The function depends on the scene depth distribution as well as on the radiometry of the scene. In order to calibrate and deploy such camera-based atmospheric visibility estimations, we present two methods-which aim at computing the scene depth distribution and the radiometry of the scene beforehand. The scene depth is recovered by registering a full 3D model of the environment in the frame of the camera. The radiometry of the scene is partly recovered by looking at the temporal correlation between the variation of pixels intensity and the variation of the sky luminance estimated by a luminance meter oriented toward the North direction. Based on clear-sky models, it is demonstrated that such a process detects a set of pixels, which include pixels belonging to North-oriented Lambertian surfaces. This finding leads to a simplified way of detecting Lambertian surfaces without any additional luminance meter. Good results obtained experimentally prove that such techniques are relevant to estimate the atmospheric visibility distance. Numéro de notice : C2011-067 Affiliation des auteurs : MATIS+Ext (1993-2011) Autre URL associée : vers pdf auteur Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICCVW.2011.6130246 Date de publication en ligne : 16/01/2012 En ligne : https://doi.org/10.1109/ICCVW.2011.6130246 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101224 Estimating meteorological visibility using cameras: A probabilistic model-driven approach / Nicolas Hautière (2011)
Titre : Estimating meteorological visibility using cameras: A probabilistic model-driven approach Type de document : Article/Communication Auteurs : Nicolas Hautière, Auteur ; Raouf Babari, Auteur ; Eric Dumont, Auteur ; Roland Brémont, Auteur ; Nicolas Paparoditis , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2011 Collection : Lecture notes in Computer Science, ISSN 0302-9743 num. 6495 Conférence : ACCV 2010, 10th Asian Conference on Computer Vision 08/11/2010 12/11/2010 Queenstown Nouvelle-Zélande Proceedings Springer Importance : pp 243 - 254 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] données météorologiques
[Termes IGN] éclairement lumineux
[Termes IGN] modèle stochastique
[Termes IGN] projection Lambert
[Termes IGN] visibilitéRésumé : (auteur) Estimating the atmospheric or meteorological visibility distance is very important for air and ground transport safety, as well as for air quality. However, there is no holistic approach to tackle the problem by camera. Most existing methods are data-driven approaches, which perform a linear regression between the contrast in the scene and the visual range estimated by means of reference additional sensors. In this paper, we propose a probabilistic model-based approach which takes into account the distribution of contrasts in the scene. It is robust to illumination variations in the scene by taking into account the Lambertian surfaces. To evaluate our model, meteorological ground truth data were collected, showing very promising results. This works opens new perspectives in the computer vision community dealing with environmental issues. Numéro de notice : C2010-054 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-642-19282-1_20 En ligne : https://doi.org/10.1007/978-3-642-19282-1_20 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101400