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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
P.910, I.T.R.: Subjective video quality assessment methods for multimedia applications. Recommendations of the ITU, Telecommunications Sector
Wolf, S., Pinson, M.H.: Spatial-temporal distortion metrics for in-service quality monitoring of any digital video system. In: Proceedings of SPIE International Symposium on Voice, Video, and Data Communications, Boston, MA (September 1999)
Ashmawi, W., Guerin, R., Wolf, S., Pinson, M.H.: On the impact of policing and rate guarantees in Diff-Serv networks: A video streaming application perspective. In: Proceedings of SIGCOMM 2001, San Diego, CA (August 2001)
Clark, A.D.: Modeling the effects of burst packet loss and recency on subjective voice quality. In: Proceedings of the IP Telephony Workshop, New York (March 2001)
Calyam, P., Mandrawa, W., Sridharan, M., Khan, A., Schopis, P.: H.323 Beacon: An H.323 application related end-to-end performance troubleshooting tool. In: Proceedings of NeTS 2004, Portland, OR (October 2004)
G.107, I.T.R.: The Emodel, a computational model for use in transmission planning. Recommendations of the ITU, Telecommunications Sector (1998)
Wang, Y., Claypool, M., Zuo, Z.: An empirical study of RealVideo performance across the Internet. In: Proceedings of IMW 2001, San Francisco, CA (November 2001)
Loguinov, D., Radha, H.: Measurement study of low-bitrate Internet video streaming. In: Proceedings of IMW 2001, San Francisco, CA (November 2001)
Nichols, J., Claypool, M., Kinicki, R., Li, M.: Measurement of the congestion responsiveness of Windows streaming media. In: Proceedings of NOSSDAV, Kinsdale, Ireland (June 2004)
Csizmar Dalal, A., Musicant, D.R., Olson, J., McMenamy, B., Benzaid, S., Kazez, B., Bolan, E.: Predicting user-perceived quality ratings from streaming media data. In: Proceedings of ICC 2007, Glasgow, Scotland (June 2007)
Csizmar Dalal, A., Olson, J.: Feature selection for prediction of user-perceived streaming media quality. In: Proceedings of SPECTS 2007, San Diego, CA (July 2007)
Csizmar Dalal, A.: User-perceived quality assessment of streaming media using reduced feature sets. Technical report, Carleton College (April 2009)
Hand, D., Mannila, H., Smyth, P.: Principles of Data Mining. MIT Press, Cambridge (2001)
Dunham, M.H.: Data Mining: Introductory and Advanced Topics. Prentice Hall, Englewood Cliffs (2002)
Tan, P., Steinbach, M., Kumar, V.: Introduction to Data Mining. Addison-Wesley, Reading (2005)
Vlachos, M., Hadjieleftheriou, M., Gunopulos, D., Keogh, E.: Indexing multi-dimensional time-series with support for multiple distance measures. In: KDD 2003, pp. 216–225. ACM Press, New York (2003)
Keogh, E., Ratanamahatana, C.: Exact indexing of dynamic time warping. Knowledge and Information Systems 7(3), 358–386 (2005)
Sakoe, H., Chiba, S.: Dynamic programming algorithm optimization for spoken word recognition. IEEE Trans. Acoustics Speech Signal Process 26, 43–49 (1978)
Carson, M., Santay, D.: NIST Net: a Linux-based network emulation tool. SIGCOMM Comput. Commun. Rev. 33(3), 111–126 (2003)
Krosnick, J.A., Fabrigar, L.R.: Designing rating scales for effective measurement in surveys. In: Survey Measurement and Process Quality, pp. 141–165. Wiley-Interscience, Hoboken (1997)
Tang, R., William, M., Shaw, J., Vevea, J.L.: Towards the identification of the optimal number of relevance categories. Journal of the American Society for Information Science 50(3), 254–264 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-642-10625-5_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10624-8
Online ISBN: 978-3-642-10625-5
eBook Packages: Computer ScienceComputer Science (R0)