Abstract
QUB-PHEO introduces a visual-based, dyadic dataset with the potential of advancing human-robot interaction (HRI) research in assembly operations and intention inference. This dataset captures rich multimodal interactions between two participants, one acting as a 'robot surrogate,' across a variety of assembly tasks that are further broken down into 36 distinct subtasks. With rich visual annotations, such as facial landmarks, gaze, hand movements, object localization, and more for 70 participants, QUB-PHEO offers two versions: full video data for 50 participants and visual cues for all 70. Designed to improve machine learning models for HRI, QUB-PHEO enables deeper analysis of subtle interaction cues and intentions, promising contributions to the field. The dataset will be available at this https URL subject to an End-User License Agreement (EULA).
Abstract (translated)
QUB-PHEO 是一个基于视觉的、二元数据集，具有推动人机交互（HRI）研究的发展以及装配操作和意图推理的潜力。这个数据集捕捉了两个参与者之间丰富的多模态互动，其中一个是“机器人代理”，在各种装配任务中进行操作。数据集进一步细分为 36 个不同的子任务。有了丰富的视觉注释，例如面部特征、眼神、手部动作、物体定位等，对于 70 名参与者，QUB-PHEO 提供了两种版本：对于 50 名参与者的完整视频数据，以及所有 70 名参与者的视觉提示。旨在提高 HRI 机器学习模型的性能，QUB-PHEO 使得对微妙的互动提示和意图进行更深刻的分析，为该领域做出贡献。数据集将在此链接上提供，受最终用户许可协议（EULA）约束。
URL
https://arxiv.org/abs/2409.15560
