Working group 3: Pierre Lepetit – Estimation of visibility and snow height on webcam images with learning to rank approach

L’Atelier interne « SCAI & AI4Climate » réunit les chercheurs, ingénieurs, doctorants, post doctorants concernés par les thématiques liées à conception et l’utilisation de nouvelles méthodes d’Intelligence Artificielle pour l’étude de l’environnement, allant du modèle à l’observation. Les premières réunions seront consacrées aux travaux des doctorants. L’exposé sera suivi d’une discussion avec les participants sur l’approche et les perspectives possibles du travail. 

16 Mars à 10h
sur le campus de Jussieu,
Salle de réunion SCAI
Batiment Esclangon 1er étage

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• The image-based estimation of meteorological parameters provides clear benefits for surface weather observation. When a local event arises, as a dense fog or a snow settling, webcams and CCTV cameras are sources of valuable information. These images actually inform about the class of weather (sunny, rainy, foggy, snowy, etc). They also enable to gauge quantitative parameters as the horizontal visibility (the farest you can see), the snow height, the precipitation rate, etc, with a variable precision.
• Recently, the weather classification task has been successfully addressed by deep learning approaches. However, the quantitative estimation faces a strong difficulty: the existing data sets that contain both images and precise weather measurements are rare and involve only few different outdoor scenes. It is virtually impossible for an expert to assign image-wise quantitative labels, but it is possible to compare two images from the same webcam and therefore assign pairwise labels. An “uncomparable” label being assigned to couples for which the expert is not able to distinguish the two images with respect to the parameter.
• This analysis gives the starting point of the workshop. The discussion will deal with the methods of labeling, learning to rank and calibration that may help to yield such comparisons and to predict ordinal or quantitative estimations of visibility and snow height. The way uncomparable pairs could lead to predict an image-wise uncertainty will also be addressed.

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https://zoom.us/j/98278319724

ID de réunion : 982 7831 9724

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