公开了实验室水波极化图像与波高计同步数据集，支持高时空分辨率波面测量。
Dataset of polarimetric images of mechanically generated water surface waves coupled with surface elevation records by wave gauges linear array
- 用偏振相机+机器学习实现水波面高精度测量
- 覆盖单色波、不规则波及破波场景，含多视角数据
- 适合海洋工程与视觉测波研究者使用
实验室中对水表面高程（水波）进行有效时空测量对于科研与工程至关重要。现有技术常繁琐、计算量大且波数/频率响应有限。为此，本文提出一种新方法，以配备偏振滤光片的相机为主要传感器，结合机器学习算法进行数据处理[1,2]。该方法的训练与评估基于自研的监督数据集。本文发布该数据集，包含机械生成水波的偏振图像及线性排列电阻式波高计（WG）记录的水面高程数据。水波在实验室波池中生成，偏振图像由人工光源拍摄。通过精密相机与波高计校准及设备同步，实现了高时空分辨率。数据涵盖多种波场条件：不同陡度的单色波列、符合JONSWAP谱形的不规则波场，以及多个波破裂场景。数据在多个相机位置相对于波传播方向重复采集。
原文摘要 · Abstract (English)
Effective spatio-temporal measurements of water surface elevation (water waves) in laboratory experiments are essential for scientific and engineering research. Existing techniques are often cumbersome, computationally heavy and generally suffer from limited wavenumber/frequency response. To address these challenges a novel method was developed, using polarization filter equipped camera as the main sensor and Machine Learning (ML) algorithms for data processing [1,2]. The developed method training and evaluation was based on in-house made supervised dataset. Here we present this supervised dataset of polarimetric images of the water surface coupled with the water surface elevation measurements made by a linear array of resistance-type wave gauges (WG). The water waves were mechanically generated in a laboratory waves basin, and the polarimetric images were captured under an artificial light source. Meticulous camera and WGs calibration and instruments synchronization supported high spatio-temporal resolution. The data set covers several wavefield conditions, from simple monochromatic wave trains of various steepness, to irregular wavefield of JONSWAP prescribed spectral shape and several wave breaking scenarios. The dataset contains measurements repeated in several camera positions relative to the wave field propagation direction.
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