Underwater Visual and Visual-Inertial Datasets (UVVID)

UVVIDThe Underwater Visual and Visual-Inertial Dataset (UVVID) contains various forms of underwater video imagery of roughly planar environments (walls and seabottom). Datasets are split between visual-only (i.e. just video data), or visual-inertial (i.e. including IMU stabilization files for the cameras). The datasets are provided as-is for testing and development of algorithms using concepts in visual odometry, SLAM, mosaicking and other mapping applications.Datasets also include post-processed forms of external data sources, such as AQUALOC and the Underwater Caves Dataset. These are provided as updated versions of the datasets that include additional transformations and sensor fusion methods to reduce ambiguity in the preprocessing methods supporting the target applications. Please see the README.md files in each subfolder for descriptions of specific datasets.ReferencesFerrera M, Creuze V, Moras J, Trouvé-Peloux P. AQUALOC: An underwater dataset for visual–inertial–pressure localization. <i>The International Journal of Robotics Research</i>. 2019;38(14):1549-1559. doi:10.1177/0278364919883346Mallios, A.; Vidal, E.; Campos, R. &amp; Carreras, M. Underwater caves sonar data set. <i>The International Journal of Robotics Research,</i><i> </i><b>2017</b><i>, 36</i>, 1247-1251<br>doi: 10.1177/0278364917732838<br>

UVVID（水下视觉与视觉惯性数据集，Underwater Visual and Visual-Inertial Dataset）涵盖各类适用于近似平面环境（墙体与海底）的水下视频影像。数据集分为纯视觉子集（仅包含视频数据）与视觉惯性子集（包含相机的惯性测量单元（Inertial Measurement Unit，IMU）稳定文件）两类。本数据集按"原样"提供，用于测试与开发基于视觉里程计（Visual Odometry）、同步定位与建图（Simultaneous Localization and Mapping，SLAM）、图像拼接（Mosaicking）及其他制图应用相关算法的研究工作。

数据集还包含经过后处理的外部数据源，例如AQUALOC与水下洞穴数据集（Underwater Caves Dataset）。此类数据集以更新版本的形式发布，其中加入了额外的变换与传感器融合方法，以降低支撑目标应用的预处理流程中的歧义性。如需了解特定数据集的详细说明，请参阅各子文件夹中的README.md文件。

参考文献
1. Ferrera M, Creuze V, Moras J, Trouvé-Peloux P. AQUALOC：一款用于视觉-惯性-压力定位的水下数据集[J]. 国际机器人研究学报（The International Journal of Robotics Research）, 2019, 38(14): 1549-1559. DOI: 10.1177/0278364919883346
2. Mallios A, Vidal E, Campos R, Carreras M. 水下洞穴声呐数据集[J]. 国际机器人研究学报（The International Journal of Robotics Research）, 2017, 36: 1247-1251. DOI: 10.1177/0278364917732838