Subjective Quality Assessment
Quality Assessment research strongly depends upon subjective experiments to provide calibration data as well as a testing mechanism. After all, the goal of all QA research is to make quality predictions that are in agreement with subjective opinion of human observers. In order to calibrate QA algorithms and test their performance, a data set of images and videos whose quality has been ranked by human subjects is required. The QA algorithm may be trained on part of this data set, and tested on the rest.
Our lab dedicates on several Perceptual Quality Experiments. Among them are impact of packet loss, temporal and quantization artifacts. We release the fallowing data set for research purpose and further reference to those who are interested in this topic.