The RCQoEA-360VR dataset is a novel multi-modal dataset designed for continuous QoE evaluation in virtual reality (VR) environments. The dataset contains continuous QoE annotations, synchronised physiological signals (ECG and GSR), behavioural data (eye and head movements) and post-viewing QoE ratings gathered through a within-VR interface from 32 participants. RCQoEA-360VR addresses a critical gap in existing public datasets by providing a fine-grained, synchronised multimodal data for immersive QoE analysis, as well as behavioural modelling, adaptive streaming, and implicit perceptual analysis.
The RCQoEA-360VR folder contains the following six subfolders
1.Behavioral_Data
2.Physiological_Data
3.QoE_Annotation_Data
4.Questionnaires
5.Scripts
6.Stimuli
The following is a detailed description of each sub-file:
- Behavioral_Data
- EM_Data contains the raw eye movement captured from each participant
- HM_Data contains the raw head movement captured from each participant
- Physiological_Data
- ECG contains the raw and processed ECG data captured from Polar H10 chest belt for each participant
- GSR contains the raw and processed GSR data captured from Shimmer GSR device for each participant
- QoE_Annotation_Data
- Continuous_QoE_Score contains the continuous QoE annotation data captured from the touch-pad for each participant
- Post_Video_QoE_Score contains the post-video QoE scores captured using within-VR interface for each participant
- Questionnaires
- contains questionnaire data (IPQ, SSQ, NASA TLX and participant information) for each participant
- Scripts
- Physiological_DataPreprocessing contains the code (python scripts) used for preprocessing the acquired raw data.
- Unity_RCQoEA contains the Unity scripts used for the experiment
- Stimuli
- contains the videos (mp4 format) used in the experiment
The RCQoEA-360VR Dataset Description.pdf introduces the dataset description and key steps in the stage of data acquisition and pre-processing.
RCQoEA-360VR dataset is licensed under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.
We have performed the time alignment of different types of data and videos for each participant. Researchers can use the data for the analysis (using AI techniques) of continuous QoE annotation or post-viewing QoE data based on physiological and behavioral signals.