@inproceedings{bc398e33eab44f77be725daffb211b32,
title = "Video-based hydrometry: A Bayesian camera calibration method for uncertainty analysis",
abstract = "Large-scale image velocimetry applications have become increasingly popular for measuring surface flow velocities and river discharges. Image orthorectification is a key step in the process and the resulting velocity and discharge uncertainty remains difficult to estimate. A novel Bayesian camera calibration method is proposed to combine prior knowledge on camera parameters and ground reference points. The method is tested using a typical crowd-sourced flood video. The parametric and structural uncertainty components due to camera calibration can be combined with other sources of errors (stage, velocity coefficient, bed shift, etc.) to build an uncertainty budget.",
author = "\{Le Coz\}, J. and B. Renard and V. Vansuyt and A. Hauet and M. Jodeau",
note = "Publisher Copyright: {\textcopyright} 2020 Taylor \& Francis Group, London; 10th Conference on Fluvial Hydraulics, River Flow 2020 ; Conference date: 07-07-2020 Through 10-07-2020",
year = "2020",
month = jan,
day = "1",
language = "English",
series = "River Flow 2020 - Proceedings of the 10th Conference on Fluvial Hydraulics",
publisher = "CRC Press/Balkema",
pages = "1053--1060",
editor = "Wim Uijttewaal and Franca, \{Mario J.\} and Daniel Valero and Victor Chavarrias and Arbos, \{Claudia Ylla\} and Ralph Schielen and Ralph Schielen and Alessandra Crosato",
booktitle = "River Flow 2020 - Proceedings of the 10th Conference on Fluvial Hydraulics",
}