Crossroad Camera Dataset - Mobility Aid Users

The most vulnerable group of traffic participants are pedestrians using mobility aids. While there has been significant progress in the robustness and reliability of camera based general pedestrian detection systems, pedestrians reliant on mobility aids are highly underrepresented in common datasets for object detection and classification. To bridge this gap and enable research towards robust and reliable detection systems which may be employed in traffic monitoring, scheduling, and planning, we present this dataset of a pedestrian crossing scenario taken from an elevated traffic monitoring perspective together with ground truth annotations (Yolo format [1]). Classes present in the dataset are pedestrian (without mobility aids), as well as pedestrians using wheelchairs, rollators/wheeled walkers, crutches, and walking canes. The dataset comes with official training, validation, and test splits. An in-depth description of the dataset can be found in [2]. If you make use of this dataset in your work, research or publication, please cite this work as: @inproceedings{mohr2023mau,author = {Mohr, Ludwig and Kirillova, Nadezda and Possegger, Horst and Bischof, Horst},title = {{A Comprehensive Crossroad Camera Dataset of Mobility Aid Users}},booktitle = {Proceedings of the 34th British Machine Vision Conference ({BMVC}2023)},year = {2023}} Archive mobility.zip contains the full detection dataset in Yolo format with images, ground truth labels and meta data, archive mobility_class_hierarchy.zip contains labels and meta files (Yolo format) for training with class hierarchy using e.g. the modified version of Yolo v5/v8 available under [3].To use this dataset with Yolo, you will need to download and extract the zip archive and change the path entry in dataset.yaml to the directory where you extracted the archive to. [1] https://github.com/ultralytics/ultralytics[2] coming soon[3] coming soon

搜集汇总

背景与挑战

背景概述

该数据集专注于使用助行器的行人，提供交通监控场景下的图像和标注，旨在改善这类行人在目标检测和分类任务中的代表性不足问题。数据集包含多种助行器使用者的类别，并提供了官方的训练、验证和测试分割，适用于交通监控、调度和规划的研究。