QoE analysis for scalable video adaptation

Abstract

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.