QoE analysis for scalable video adaptation
Quality of Experience (QoE) serves as a key service goal in video applications. In this paper, we study the QoE issue in scalable video adaptation by constructing a subjective video quality assessment database based on the full scalability of SVC. We derive the optimal scalability adaptation track f...
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sg-ntu-dr.10356-977502020-03-07T13:24:48Z QoE analysis for scalable video adaptation Li, Maodong Chen, Zhenzhong Tan, Yap Peng School of Electrical and Electronic Engineering IEEE Visual Communications and Image Processing (2012 : San Diego, US) DRNTU::Engineering::Electrical and electronic engineering Quality of Experience (QoE) serves as a key service goal in video applications. In this paper, we study the QoE issue in scalable video adaptation by constructing a subjective video quality assessment database based on the full scalability of SVC. We derive the optimal scalability adaptation track for individual video and further summarize common scalability adaptation tracks for grouped videos. The common track provides useful guidelines on how to adapt scalable video based on their content characteristics. A rate-QoE model is proposed accordingly for the SVC adaptation. Experimental analyses show that the novel QoE-aware scalability adaptation scheme significantly outperforms the existing ones. 2013-07-25T02:28:31Z 2019-12-06T19:46:06Z 2013-07-25T02:28:31Z 2019-12-06T19:46:06Z 2012 2012 Conference Paper Li, M., Chen, Z., & Tan, Y. P. (2012). QoE analysis for scalable video adaptation. 2012 IEEE Visual Communications and Image Processing (VCIP). https://hdl.handle.net/10356/97750 http://hdl.handle.net/10220/12153 10.1109/VCIP.2012.6410787 en © 2012 IEEE. |
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DRNTU::Engineering::Electrical and electronic engineering Li, Maodong Chen, Zhenzhong Tan, Yap Peng QoE analysis for scalable video adaptation |
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Quality of Experience (QoE) serves as a key service goal in video applications. In this paper, we study the QoE issue in scalable video adaptation by constructing a subjective video quality assessment database based on the full scalability of SVC. We derive the optimal scalability adaptation track for individual video and further summarize common scalability adaptation tracks for grouped videos. The common track provides useful guidelines on how to adapt scalable video based on their content characteristics. A rate-QoE model is proposed accordingly for the SVC adaptation. Experimental analyses show that the novel QoE-aware scalability adaptation scheme significantly outperforms the existing ones. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Li, Maodong Chen, Zhenzhong Tan, Yap Peng |
format |
Conference or Workshop Item |
author |
Li, Maodong Chen, Zhenzhong Tan, Yap Peng |
author_sort |
Li, Maodong |
title |
QoE analysis for scalable video adaptation |
title_short |
QoE analysis for scalable video adaptation |
title_full |
QoE analysis for scalable video adaptation |
title_fullStr |
QoE analysis for scalable video adaptation |
title_full_unstemmed |
QoE analysis for scalable video adaptation |
title_sort |
qoe analysis for scalable video adaptation |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/97750 http://hdl.handle.net/10220/12153 |
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1681037672147058688 |