What's wrong with mean-squared error?
Digital images and human vision
QoE oriented cross-layer design of a resource allocation algorithm in beyond 3G systems
Computer Communications
Q-DRAM: QoE-based dynamic rate adaptation mechanism for multicast in wireless networks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Qoe-based rate adaptation scheme selection for resource-constrained wireless video transmission
Proceedings of the international conference on Multimedia
3D video transcoding for virtual views
Proceedings of the international conference on Multimedia
A multi-pass VBR rate control method for video plus depth based mobile 3D video coding
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
Error resilience video transcoding for wireless communications
IEEE Wireless Communications
A study of real-time packet video quality using random neural networks
IEEE Transactions on Circuits and Systems for Video Technology
Rate-distortion analysis for H.264/AVC video coding and its application to rate control
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Quality adaptation in p2p video streaming based on objective qoe metrics
IFIP'12 Proceedings of the 11th international IFIP TC 6 conference on Networking - Volume Part II
Hi-index | 0.00 |
With advance in mobile 3D display, mobile 3D video is already enabled by the wireless multimedia networking, and it will be gradually popular since it can make people enjoy the natural 3D experience anywhere and anytime. In current stage, mobile 3D video is generally delivered over the heterogeneous network combined by wired and wireless channels. How to guarantee the optimal 3D visual quality of experience (QoE) for the mobile 3D video streaming is one of the important topics concerned by the service provider. In this article, we propose a QoE-oriented transcoding approach to enhance the quality of mobile 3D video service. By learning the pre-controlled QoE patterns of 3D contents, the proposed 3D visual QoE inferring model can be utilized to regulate the transcoding configurations in real-time according to the feedbacks of network and user-end device information. In the learning stage, we propose a piecewise linear mean opinion score (MOS) interpolation method to further reduce the cumbersome manual work of preparing QoE patterns. Experimental results show that the proposed transcoding approach can provide the adapted 3D stream to the heterogeneous network, and further provide superior QoE performance to the fixed quantization parameter (QP) transcoding and mean squared error (MSE) optimized transcoding for mobile 3D video streaming.