Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
A model-driven approach to estimate atmospheric visibility with ordinary cameras
Abstract 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.
Highlights ► A model-driven approach to monitor atmospheric visibility distance by camera. ► A method robust to illumination variations by selecting the Lambertian surfaces. ► A physics-based model which maps the contrast and the atmospheric visibility. ► A novel data fitting process limited to a reliable subset of the data.
A model-driven approach to estimate atmospheric visibility with ordinary cameras
Abstract 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.
Highlights ► A model-driven approach to monitor atmospheric visibility distance by camera. ► A method robust to illumination variations by selecting the Lambertian surfaces. ► A physics-based model which maps the contrast and the atmospheric visibility. ► A novel data fitting process limited to a reliable subset of the data.
A model-driven approach to estimate atmospheric visibility with ordinary cameras
Babari, Raouf (Autor:in) / Hautière, Nicolas (Autor:in) / Dumont, Éric (Autor:in) / Brémond, Roland (Autor:in) / Paparoditis, Nicolas (Autor:in)
Atmospheric Environment ; 45 ; 5316-5324
18.06.2011
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Automatic Visibility Measurement Methods Based on Video Cameras
| British Library Conference Proceedings | 1998
Estimating the Value of Atmospheric Visibility
| British Library Conference Proceedings | 1992
Reconstructing atmospheric cloud particles from multiple fisheye cameras
| British Library Online Contents | 2018