Dataset for Drone-based Inspection of Road Pavement Structures for Cracks

The dataset is available online as a benchmarking dataset for drone-based inspection of pavement structures. The data were acquired in an experimental road with a length of 386 meters, belonging to Montmorency Forest laboratory of Université Laval, located in North of Quebec City, on 2021/06/16. The road is mainly used for testing pavement paints, laying techniques, and inspection simulations. A DJI MINI 2 drone was employed to collect images for this dataset. The drone has a 12 megapixels camera with an 83 degrees field of view, capturing 1920 x 1080 images in the continuous recording mode. The drone performs six passes on an experimental road at different altitudes and horizontal speeds. The drone was controlled manually, and the footage was acquired using the embedded camera that stabilized and controlled using the drone's gimbal. Moreover, after data acquisition, the length and width of some cracks and road landmarks were measured for evaluating crack characterization. **** In case of any use, please cite this dataset and our paper ****

本数据集作为无人机路面结构巡检基准数据集可在线获取。数据采集于2021年6月16日，采集场地为位于魁北克市北部、隶属于拉瓦尔大学（Université Laval）蒙莫朗西森林实验室（Montmorency Forest laboratory）的一段长386米的试验路段。该路段主要用于路面涂料、摊铺工艺及巡检模拟测试。本次数据集采用DJI MINI 2无人机采集图像，该无人机搭载1200万像素摄像头，视场角为83°，可在连续录制模式下采集分辨率为1920×1080的图像。无人机在试验路段以不同飞行高度和水平飞行速度完成6次飞越作业，全程采用手动操控，影像由搭载的、受无人机云台稳定控制的内置摄像头采集。此外，数据采集完成后，还对部分裂缝与道路地标物的长宽尺寸进行了测量，用于裂缝表征性能的评估。若需使用本数据集，请引用本数据集及相关研究论文。

搜集汇总

背景与挑战

背景概述

该数据集是一个用于无人机检测道路路面裂缝的基准数据集，包含在实验道路上采集的高分辨率图像数据，覆盖不同飞行高度和速度条件下的六次飞行记录，并提供了裂缝和道路标志的尺寸测量数据。