Paper Info
Title
Content classification-based and QoE-driven video send bitrate adaptation scheme
Abstract
Initial video quality requirement is not well understood and content providers usually send video at the highest send bitrate resulting in over-provisioning. The main aim of this paper is to present a new scheme that can adapt video send bitrate according to the dynamics of the content and the user's Quality of Experience (QoE) requirement at the pre-encoding stage. Contents are classified based on their spatio-temporal feature extraction. Video quality is predicted in terms of the Peak-Signal-to-Noise-Ratio (PSNR). Statistical analysis of the experimental results confirms that the proposed adaptation scheme performs well for all content types and hence, improves the perceived end-to-end video quality. The proposed scheme makes it possible for content providers to achieve an optimum streaming scheme (with an appropriate send bitrate) suitable for the content type for a requested QoE.
Year
DOI
Venue
2009
10.4108/ICST.MOBIMEDIA2009.7687
MobiMedia
Keywords
Field
DocType
psnr
Content type,Average bitrate,Computer science,Constant bitrate,Feature extraction,Real-time computing,Quality of experience,Multimedia,Video quality,Statistical analysis,Variable bitrate
Conference
Citations 
PageRank 
References 
3
0.54
8
Authors
4
Name
Order
Citations
PageRank
Asiya Khan123214.47
Lingfen Sun241838.26
Emmanuel Jammeh31459.17
Emmanuel C. Ifeachor425526.56