Skip to main content

Research Repository

Advanced Search

Scalable Remote Rendering using Synthesized Image Quality Assessment

Wang, Xiaochuan; Liang, Xiaohui; Yang, Bailin; Li, Frederick W.B.

Scalable Remote Rendering using Synthesized Image Quality Assessment Thumbnail


Xiaochuan Wang

Xiaohui Liang

Bailin Yang


Depth-image-based rendering (DIBR) is widely used to support 3D interactive graphics on low-end mobile devices. Although it reduces the rendering cost on a mobile device, it essentially turns such a cost into depth image transmission cost or bandwidth consumption, inducing performance bottleneck to a remote rendering system. To address this problem, we design a scalable remote rendering framework based on synthesized image quality assessment. Specially, we design an efficient synthesized image quality metric based on Just Noticeable Distortion (JND), properly measuring human perceived geometric distortions in synthesized images. Based on this, we predict quality-aware reference viewpoints, with viewpoint intervals optimized by the JND-based metric. An adaptive transmission scheme is also developed to control depth image transmission based on perceived quality and network bandwidth availability. Experiment results show that our approach effectively reduces transmission frequency and network bandwidth consumption with perceived quality on mobile devices maintained. A prototype system is implemented to demonstrate the scalability of our proposed framework to multiple clients.


Wang, X., Liang, X., Yang, B., & Li, F. W. (2018). Scalable Remote Rendering using Synthesized Image Quality Assessment. IEEE Access, 6, 36595-36610.

Journal Article Type Article
Acceptance Date Jun 29, 2018
Online Publication Date Jul 5, 2018
Publication Date Jul 25, 2018
Deposit Date Jul 7, 2018
Publicly Available Date Aug 1, 2018
Journal IEEE Access
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 6
Pages 36595-36610


Published Journal Article (2.5 Mb)

Copyright Statement
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

You might also like

Downloadable Citations