DocumentCode :
8276
Title :
From QoS to QoE: A Tutorial on Video Quality Assessment
Author :
Yanjiao Chen ; Kaishun Wu ; Qian Zhang
Author_Institution :
Dept. of Comput. Sci. & Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, China
Volume :
17
Issue :
2
fYear :
2015
fDate :
Secondquarter 2015
Firstpage :
1126
Lastpage :
1165
Abstract :
Quality of experience (QoE) is the perceptual quality of service (QoS) from the users´ perspective. For video service, the relationship between QoE and QoS (such as coding parameters and network statistics) is complicated because users´ perceptual video quality is subjective and diversified in different environments. Traditionally, QoE is obtained from subjective test, where human viewers evaluate the quality of tested videos under a laboratory environment. To avoid high cost and offline nature of such tests, objective quality models are developed to predict QoE based on objective QoS parameters, but it is still an indirect way to estimate QoE. With the rising popularity of video streaming over the Internet, data-driven QoE analysis models have newly emerged due to availability of large-scale data. In this paper, we give a comprehensive survey of the evolution of video quality assessment methods, analyzing their characteristics, advantages, and drawbacks. We also introduce QoE-based video applications and, finally, identify the future research directions of QoE.
Keywords :
Internet; quality of experience; statistical analysis; video streaming; Internet; QoS; coding parameters; data-driven QoE analysis model; large-scale data; network statistics; quality of experience; video quality assessment tutorial; video streaming; Bit rate; Delays; Jitter; Quality assessment; Quality of service; Streaming media; Video recording; Data-driven Analysis; Objective Quality Model; Quality of Experience; Quality of experience; Subjective Test; data-driven analysis; objective quality model; subjective test;
fLanguage :
English
Journal_Title :
Communications Surveys & Tutorials, IEEE
Publisher :
ieee
ISSN :
1553-877X
Type :
jour
DOI :
10.1109/COMST.2014.2363139
Filename :
6933929
Link To Document :
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