Abstract
Scalable video coding of H.264/AVC standard enables adaptive and flexible delivery for multiple devices and various network conditions. Only a few works have addressed the influence of different scalability parameters (frame rate, spatial resolution, and SNR) on the user perceived quality within a limited scope. In this paper, we have conducted an experiment of subjective quality assessment for video sequences encoded with H.264/SVC to gain a better understanding of the correlation between video content and UPQ at all scalable layers and the impact of rate-distortion method and different scalabilities on bitrate and UPQ. Findings from this experiment will contribute to a user-centered design of adaptive delivery of scalable video stream.
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
Schwarz, H., Marpe, D., Wiegand, T.: Overview of the scalable video coding extension of the H.264/AVC standard. IEEE Transactions on Circuits and Systems for Video Technology 17, 1103–1120 (2007)
Ahmad, A.M.A.: Content-based Video Streaming Approaches and Challenges. In: Ibrahim, I.K. (ed.) Handbook of Research on Mobile Multimedia, pp. 357–367. Idea group Reference, London (2006)
Ries, M., Crespi, C., Nemethova, O., Rupp, M.: Content based video quality estimation for H.264/AVC video streaming. In: IEEE WCNC 2007, pp. 2668–2673. IEEE Press, Los Alamitos (2007)
Wang, Y., van der Schaar, M., Chang, S.-F., Loui, A.C.: Classification-based multidimensional adaptation prediction for scalable video coding using subjective quality evaluation. IEEE Transactions on Circuits and Systems for Video Technology 15, 1270–1279 (2005)
Wang, D., Speranza, F., Vincent, A., Martin, T., Blanchfield, P.: Toward optimal rate control: a study of the impact of spatial resolution, frame rate, and quantization on subjective video quality and bit rate. In: Visual Communications and Image Processing 2003, vol. 5150, pp. 198–209. SPIE (2003)
McCarthy, J.D., Sasse, M.A., Miras, D.: Sharp or smooth?: Comparing the effects of quantization vs. frame rate for streamed video. In: SIGCHI conference on Human factors in computing systems, pp. 535–542. ACM, New York (2004)
Zhai, G., Cai, J., Lin, W., Yang, X., Zhang, W., Etoh, M.: Cross-Dimensional perceptual quality assessment for low Bit-Rate videos. IEEE Transactions on Multimedia 10, 1316–1324 (2008)
Niedermeier, F., Niedermeier, M., Kosch, H.: Quality assessment of MPEG-4 scalable video CODEC. In: ICIAP2009. LNCS, vol. 5716, pp. 297–306. Springer, Heidelberg (2009)
ITU-T: Subjective video quality assessment methods for multimedia applications (1999)
Apteker, R.T., Fisher, J.A., Kisimov, V.S., Neishlos, H.: Video acceptability and frame rate. IEEE Multimedia 2, 32–40 (1995)
Van der Auwera, G., David, P.T., Reisslein, M.: Traffic and quality characterization of single-layer video streams encoded with the H.264/MPEG-4 advanced video coding standard and scalable video coding extension. IEEE Transactions on Broadcasting 54, 698–718 (2008)
Knoche, H.O., McCarthy, J.D., Sasse, M.A.: How low can you go? The effect of low resolutions on shot types in mobile TV. Multimedia Tools and Applications 36, 145–166 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Song, W., Tjondronegoro, D., Azad, S. (2010). User-Centered Video Quality Assessment for Scalable Video Coding of H.264/AVC Standard. In: Boll, S., Tian, Q., Zhang, L., Zhang, Z., Chen, YP.P. (eds) Advances in Multimedia Modeling. MMM 2010. Lecture Notes in Computer Science, vol 5916. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11301-7_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-11301-7_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11300-0
Online ISBN: 978-3-642-11301-7
eBook Packages: Computer ScienceComputer Science (R0)