報告人：張景舜 作者： Gardlo, B. ； Ries, M. ; Rupp, M. ; Jarina, R. ； Dept. of Telecommun. & Multimedia, Univ. of Zilina, Zilina, Slovakia QoE Evaluation Methodology for HD Video Streaming using Social Networking

I. INTRODUCTION Quality-of-Experience (QoE) and Social networks has gained strong interest, both from a research and a commercial perspective. Assessment methodologies are extremely time consuming and poorly re fl ect ”real world” scenarios.

II. USER BASED ASSESSMENT Relationship between user, application and network. Absolute Category Rating (ACR)

II. USER BASED ASSESSMENT In fl uence factors of quality of experience(QoE)

III. CONTEXT INFLUENCE AND QOE Modern social networks rely not just on the messaging concept 46% of them are under 25 years old and another 26% is under 35 years.

III. CONTEXT INFLUENCE AND QOE A. Audiovisual content SPATIAL AND TEMPORAL CHARACTERISTICS OF CONTENT CLASSES B. Social and Cultural Aspects

IV. TECHNICAL SYSTEM A. Encoder settings Audio content was encoded using an AAC codec with 48 kHz sampling rate and 96 kbit/s bit rate. Each of these sequences was further encoded into fi ve equally distanced video bit rates, 2 Mbit/s for the best quality, and 800 kbit/s for the lowest quality (300 kbit/s step size).

IV. TECHNICAL SYSTEM B. End User Devices Targeting our QoE assessment application on the HD multimedia content, we cannot guarantee that this content will be also watched on native HD capable screens. About 50% of the users use resolutions of 1024x768, 1280x800 or similar.

V. QOE ASSESSMENT A. Statistical relevance of obtained subjective evaluations

V. QOE ASSESSMENT 評估方法 s : sample variance d : accuracy parameter (allowed error in estimation) x^: sample mean μ : true population mean n : minimum sample size

V. QOE ASSESSMENT B. Assessment results Action movie 800 kbit/s MOS Histogram. Action movie 2000kbit/s MOS Histogram.

V. QOE ASSESSMENT MOS values with their 95% con fi dence intervals.

VI. CONCLUSION The methodology provides a high applicability for subjective testing of the multimedia services with respect to real usage scenarios. With the social data available throughout the social network, we can target certain speci fi c user groups, with no need of performing exhausting social studies. All these facts support the high statistical signi fi cance of the results.