2024/09/23 by Samuel Adebayo, Adebayo, Samuel, Seán McLoone +3 · 1 citation
Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Human-Computer Interaction (cs.HC) #Image and Video Processing (eess.IV) #Manufacturing Process and Optimization #Signal Processing (eess.SP) #Software Engineering Research #Software Engineering Techniques and Practices #electronic engineering #information engineering
paper · doi:10.48550/arxiv.2409.15560
openalex publication_date 2024/09/23 · openalex created_date 2024/10/26 · openalex updated_date 2026/07/28
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 https://github.com/exponentialR/QUB-PHEO subject to an End-User License Agreement (EULA).