Impact of frame rate and resolution on objective QoE metrics

Video streaming applications are a major driver for the evolution of the future Internet. In this paper we introduce a framework for QoE management for video streaming systems based on the H.264/SVC codec, the scalable extension of H.264/AVC. A relevant feature is to control the user perceived quality of experience (QoE) by exploiting parameters offered by SVC. A proper design of a control mechanism requires the quantification of the main influence parameters on the QoE. For this purpose, we conducted a measurement study and quantified the influence of i) video resolution, ii) scaling method, iii) video frame rate and iv) video content types on the QoE by means of the SSIM and VQM full-reference metrics. Further, we discuss the trade-off between these different control knobs and their influence on the QoE.

[1]  Stefan Winkler.  Video quality and beyond , 2007, 2007 15th European Signal Processing Conference.

[2]  M. Angela Sasse,et al.  Sharp or smooth?: comparing the effects of quantization vs. frame rate for streamed video , 2004, CHI '04.

[3]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[4]  Simon Oechsner,et al.  Supporting Scalable Video Codecs in a P2P Video-on-Demand Streaming System , 2010 .

[5]  Margaret H. Pinson,et al.  A new standardized method for objectively measuring video quality , 2004, IEEE Transactions on Broadcasting.

[6]  Heiko Schwarz,et al.  Overview of the Scalable Video Coding Extension of the H.264/AVC Standard , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[7]  Daniel Schlosser,et al.  Quantifying the Influence of Network Conditions on the Service Quality Experienced by a Thin Client User , 2008, MMB.

[8]  Markus Fiedler,et al.  A generic quantitative relationship between quality of experience and quality of service , 2010, IEEE Network.

[9]  Margaret H. Pinson.  Video Quality Metric Software , 2005 .

[10]  M. Angela Sasse,et al.  The big picture on small screens delivering acceptable video quality in mobile TV , 2009, TOMCCAP.

[11]  Alan C. Bovik,et al.  A subjective study to evaluate video quality assessment algorithms , 2010, Electronic Imaging.

[12]  Zhou Wang,et al.  Video quality assessment based on structural distortion measurement , 2004, Signal Process. Image Commun..

[13]  Helmut Hlavacs,et al.  Subjective Quality of Mobile MPEG-4 Videos with Different Frame Rates , 2006, J. Mobile Multimedia.

[14]  Itu-T and Iso Iec Jtc.  Advanced video coding for generic audiovisual services , 2010 .

[15]  Biing-Hwang Juang,et al.  Subjective Evaluation of Spatial Resolution and Quantization Noise Tradeoffs , 2009, IEEE Transactions on Image Processing.

[16]  Phuoc Tran-Gia,et al.  Towards QoE Management for Scalable Video Streaming , 2011 .

[17]  Takanori Hayashi,et al.  Parametric Packet-Layer Model for Monitoring Video Quality of IPTV Services , 2008, 2008 IEEE International Conference on Communications.

[18]  Markus Fiedler,et al.  Quantification of Quality of Experience for Edge-Based Applications , 2007, ITC.