Shading Atlas Streaming

Joerg H. Mueller, Philip Voglreiter, Mark Dokter, Thomas Neff, Mina Makar, Markus Steinberger, and Dieter Schmalstieg:
ACM Transactions on Graphics (SIGGRAPH Asia'18), 2018

Game scenes (top row) with corresponding shading atlas (bottom row). The shading atlas contains all the shading information of the visible surfaces corresponding to the rendered scenes. The object-space parametrization is created fully dynamically. From the shading atlas, novel views at close viewpoints can be rendered for framerate upsampling and warping. The shading atlas is temporally coherent and lends itself to efficient MPEG compression and streaming.

Abstract

Streaming high quality rendering for virtual reality applications requires minimizing perceived latency. We introduce Shading Atlas Streaming (SAS), a novel object-space rendering framework suitable for streaming virtual reality content. SAS decouples server-side shading from client-side rendering, allowing the client to perform framerate upsampling and latency compensation autonomously for short periods of time. The shading information created by the server in object space is temporally coherent and can be efficiently compressed using standard MPEG encoding. Our results show that SAS compares favorably to previous methods for remote image-based rendering in terms of image quality and network bandwidth efficiency. SAS allows highly efficient parallel allocation in a virtualized-texture-like memory hierarchy, solving a common efficiency problem of object-space shading. With SAS, untethered virtual reality headsets can benefit from high quality rendering without paying in increased latency.

Resources

paper [pdf 12.1 MiB]

supplemental material [pdf 0.6 MiB]

presentation [pptx 46.7 MiB]

bibtex

@article{Mueller:2018:SAS,
author = {Mueller, Joerg H. and Voglreiter, Philip and Dokter, Mark and Neff, Thomas and Makar, Mina and Steinberger, Markus and Schmalstieg, Dieter},
title = {Shading Atlas Streaming},
journal = {ACM Transactions on Graphics},
issue_date = {November 2018},
volume = {37}, number = {6},
month = nov,
year = {2018},
articleno = {199},
numpages = {16},
doi = {10.1145/3272127.3275087},
publisher = {ACM},
address = {New York, NY, USA},
}