Abstract
While mechanisms exist to evaluate the user-perceived quality of video streamed over computer networks, there are few good mechanisms to do so in real time. In this paper, we evaluate the feasibility of predicting the stream quality of partial portions of a video stream based on either complete or incomplete information from previously rated streams. Using stream state information collected from an instrumented media player application and subjective stream quality ratings similar to the Mean Opinion Score, we determine whether a stream quality prediction algorithm utilizing dynamic time warping as a distance measure can rate partial streams with an accuracy on par with that achieved by the same predictor when rating full streams. We find that such a predictor can achieve comparable, and in some cases markedly better, accuracy over a wide range of possible partial stream portions, and that we can achieve this using portions of as little as ten seconds.
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© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Csizmar Dalal, A., Kawaler, E., Tucker, S. (2009). Towards Real-Time Stream Quality Prediction: Predicting Video Stream Quality from Partial Stream Information. In: Bartolini, N., Nikoletseas, S., Sinha, P., Cardellini, V., Mahanti, A. (eds) Quality of Service in Heterogeneous Networks. QShine 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 22. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10625-5_2
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DOI: https://doi.org/10.1007/978-3-642-10625-5_2
Publisher Name: Springer, Berlin, Heidelberg
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