为救援人员手势控制机器人设计首个RGBD数据集，支持多视角精准识别。
FR-GESTURE: An RGBD Dataset For Gesture-based Human-Robot Interaction In First Responder Operations
- 基于真实救援手势设计12类指令，结合专家反馈优化。
- 采集3312组双视角、7种距离的RGBD数据，覆盖多种操作场景。
- 公开数据集与评测基准，助力救援机器人交互研究。
灾难频发使救援人员工作难度持续上升，人工智能与机器人技术可有效辅助其作业。为此，我们提出一个面向救援人员手势控制无人地面机器人的RGBD数据集——FR-GESTURE，包含12类手势指令，参考现有救援手势及战术手语，并经资深救援人员反馈优化。数据采集涵盖2个视角、7种距离，共获得3312对RGBD图像。据我们所知，这是首个专为救援人员手势引导无人车设计的数据集。我们还制定了评估协议并开展了基线实验，以供后续改进。数据集已公开，网址：https://doi.org/10.5281/zenodo.18131333，推动该领域研究发展。
原文摘要 · Abstract (English)
The ever increasing intensity and number of disasters make even more difficult the work of First Responders (FRs). Artificial intelligence and robotics solutions could facilitate their operations, compensating these difficulties. To this end, we propose a dataset for gesture-based UGV control by FRs, introducing a set of 12 commands, drawing inspiration from existing gestures used by FRs and tactical hand signals and refined after incorporating feedback from experienced FRs. Then we proceed with the data collection itself, resulting in 3312 RGBD pairs captured from 2 viewpoints and 7 distances. To the best of our knowledge, this is the first dataset especially intended for gesture-based UGV guidance by FRs. Finally we define evaluation protocols for our RGBD dataset, termed FR-GESTURE, and we perform baseline experiments, which are put forward for improvement. We have made data publicly available to promote future research on the domain: https://doi.org/10.5281/zenodo.18131333.
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