CAMBER Dataset – Road Survey Video #38

This dataset contains road survey video recordings collected within the CAMBER - European Road Infrastructure Monitoring Project. The videos capture forward-facing visual information on road infrastructure condition, including pavement defects, surface degradation, and road furniture elements. **Data Generation Method:** The video was recorded using mobile devices during road monitoring campaigns. Video frames were processed using YOLO-based computer vision models to detect road malfunctions including potholes, manholes, and speed breakers. Detections were geo-referenced using synchronized GPS track data. **Type of Data:** Video / Image sequences **Data Format(s):** MP4 (video), CSV (detection results), GPX (GPS track) **Spatial Coverage:** - Geographic coordinates: WGS84 (EPSG:4326) **Temporal Coverage:** - Recording date: 2026-02-25 13:02:12 UTC **Processing Information:** - Video ID: 38 - Processing status: Pending - Safety assessment: Green (Totally Safe) - Associated Route ID: 38 **Machine Learning Model:** - Model: models/yolov8_pothole_detection.pt - Detected classes: manhole,pothole,speedbreaker,potholes - Confidence threshold: 0.45 - Minimum track age: 5 frames **Data Access:** The dataset files are stored on the CAMBER project infrastructure with S3-compatible storage. Zenodo serves as a persistent metadata record and DOI landing page. Access to the full dataset is provided via the related identifiers or upon request. **Funding:** This work was funded by the European Union under the Horizon Europe programme, Grant Agreement No. 101156387.本数据集收录自CAMBER欧洲道路基础设施监测项目（European Road Infrastructure Monitoring Project）中采集的道路勘测视频录像。所录制视频可捕获道路基础设施状况的正向视觉信息，涵盖路面缺陷、表层劣化以及道路附属设施要素。 **数据生成方式：** 本次视频通过移动设备在道路监测作业过程中录制完成。视频帧采用基于YOLO的计算机视觉模型进行处理，以检测路面故障，包括坑槽、检查井以及减速带。检测结果通过同步的GPS轨迹数据进行地理配准。 **数据类型：** 视频/图像序列 **数据格式：** MP4（视频文件）、CSV（检测结果文件）、GPX（GPS轨迹文件） **空间覆盖范围：** - 地理坐标系：WGS84（EPSG:4326） **时间覆盖范围：** - 录制日期：2026年2月25日 13时02分12秒 UTC **处理信息：** - 视频ID：38 - 处理状态：待处理 - 安全评估：绿色（完全安全） - 关联路线ID：38 **机器学习模型：** - 模型路径：models/yolov8_pothole_detection.pt - 检测类别：检查井、坑槽、减速带、坑槽 - 置信度阈值：0.45 - 最小跟踪时长：5帧 **数据获取：** 本数据集文件存储于CAMBER项目的S3兼容存储基础设施中。Zenodo平台作为持久化元数据记录与DOI落地页提供服务。完整数据集可通过相关标识符获取，或根据申请获取。 **资助信息：** 本研究由欧盟地平线欧洲（Horizon Europe）计划资助，资助协议编号为101156387。