Subjective experiment dataset for joint development of hybrid video quality measurement algorithms

Abstract : The application area of an objective measurement algorithm for video quality is always limited by the scope of the video datasets that were used during its development and training. This is particularly true for measurements which rely solely on information available at the decoder side, for example hybrid models that analyze the bitstream and the decoded video. This paper proposes a framework which enables researchers to train, test and validate their algorithms on a large database of video sequences in such a way that the - often limited - scope of their development can be taken into consideration. A freely available video database for the development of hybrid models is described containing the network bitstreams, parsed information from these bitstreams for easy access, the decoded video sequences, and subjectively evaluated quality scores.