QoE-Dataset-VLC-Indicators
This work is proposed to describe and to share a subjective QoE dataset that assess YouTube video quality in controlled
laboratory environment. This dataset is collected using the subjective Absolute Category Rate (ACR) method based on Mean Opinion Score (MOS) ratting score. It provides a good representative panel of various QoE Influence Factors (QoE IFs), that allows researchers community to work in order to study and better understand the QoE concept.
To build this dataset, a testbed is achieved in the LiSSi laboratory around Paris city in France. 62 testers participated in the test campaign. All of them were researchers and students from different disciplines aged 19 to 41 years with few or no experience with video assessment experimentation. The collected QoE IFs concerns many video parameters (QoA) that VLC video player provides as indicator.
The dataset was built from a controlled laboratory testbed where 560 sample covering 18 Quality of Experience Impact Factors (QoE IFs). The used videos are of different types/complexities.
You can download the dataset and find more details here:
https://github.com/Lamyne/QoE-Dataset-VLC-Indicators