Marcus Barkowsky, I. Sedano, K. Brunnström, M. Leszczuk, N. Staelens
Hybrid video quality prediction: reviewing video quality measurement for widening application scope
Multimedia Tools and Applications, vol. 74, pp. 323-343
A tremendous number of objective video quality measurement algorithms have been developed during the last two decades. Most of them either measure a very limited aspect of the perceived video quality or they measure broad ranges of quality with limited prediction accuracy. This paper lists several perceptual artifacts that may be computationally measured in an isolated algorithm and some of the modeling approaches that have been proposed to predict the resulting quality from those algorithms. These algorithms usually have a very limited application scope but have been verified carefully. The paper continues with a review of some standardized and well-known video quality measurement algorithms that are meant for a wide range of applications, thus have a larger scope. Their individual artifacts prediction accuracy is usually lower but some of them were validated to perform sufficiently well for standardization. Several difficulties and shortcomings in developing a general purpose model with high prediction performance are identified such as a common objective quality scale or the behavior of individual indicators when confronted with stimuli that are out of their prediction scope. The paper concludes with a systematic framework approach to tackle the development of a hybrid video quality measurement in a joint research collaboration.
Beitrag (Sammelband oder Tagungsband)
M. Leszczuk, L. Janowski, Marcus Barkowsky
Freely Available Large-scale Video Quality Assessment Database in Full-HD Resolution with H.264 Coding
Proceedings of the 2013 IEEE Globecom Workshops (GC Wkshps), Atlanta, GA, USA, no. -
Video databases often focus on a particular use case with a limited set of sequences. In this paper, a different type of database creation is proposed: an exhaustive number of test conditions will be continuously created and made freely available for objective and subjective evaluation. At the moment, the database comprises more than ten thousand JM/x264-encoded video sequences. An extensive study of the possible encoding parameter space led to a first subset selection of 1296 configura- tions. At the moment, only ten source sequences have been used, but extension to more than one hundred sequences is planned. Some Full-Reference (FR) and No-Reference (NR) metrics were selected and calculated. The resulting data will be freely available to the research community and possible exploitation areas are suggested.
Beitrag (Sammelband oder Tagungsband)
Marcus Barkowsky, N. Staelens, L. Janowski, Y. Koudota, M. Leszczuk, M. Urvoy, P. Hummelbrunner, I. Sedano, K. Brunnström
Subjective experiment dataset for joint development of hybrid video quality measurement algorithms
QoEMCS 2012 ‐ Third Workshop on Quality of Experience for Multimedia Content Sharing, Berlin
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.