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A new methodology to measure coded image/video quality using thejust-noticeable-difference (JND) idea was proposed. Several small JND-basedimage/video quality datasets were released by the Media Communications Lab atthe University of Southern California. In this work, we present an effort tobuild a large-scale JND-based coded video quality dataset. The dataset consistsof 220 5-second sequences in four resolutions (i.e., $1920 \times 1080$, $1280\times 720$, $960 \times 540$ and $640 \times 360$). For each of the 880 videoclips, we encode it using the H.264 codec with $QP=1, \cdots, 51$ and measurethe first three JND points with 30+ subjects. The dataset is called the"VideoSet", which is an acronym for "Video Subject Evaluation Test (SET)". Thiswork describes the subjective test procedure, detection and removal of outlyingmeasured data, and the properties of collected JND data. Finally, thesignificance and implications of the VideoSet to future video coding researchand standardization efforts are pointed out. All source/coded video clips aswell as measured JND data included in the VideoSet are available to the publicin the IEEE DataPort.

VideoSet: A Large-Scale Compressed Video Quality Dataset Based on JND Measurement