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Perceptual rasterization for head-mounted display image synthesis

Ritschel, T; Friston, S; Steed, A; (2019) Perceptual rasterization for head-mounted display image synthesis. ACM Transactions on Graphics , 38 (4) , Article 97. 10.1145/3306346. Green open access

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Abstract

We suggest a rasterization pipeline tailored towards the needs of HMDs, where latency and field-of-view requirements pose new challenges beyond those of traditional desktop displays. Instead of image warping for low latency, or using multiple passes for foveation, we show how both can be produced directly in a single perceptual rasterization pass. We do this with per-fragment ray-casting. This is enabled by derivations of tight space-time-fovea pixel bounds, introducing just enough flexibility for the requisite geometric tests, but retaining most of the simplicity and efficiency of the traditional rasterizaton pipeline. To produce foveated images, we rasterize to an image with spatially varying pixel density. To compensate for latency, we extend the image formation model to directly produce "rolling" images where the time at each pixel depends on its display location. Our approach overcomes limitations of warping with respect to disocclusions, object motion and view-dependent shading, as well as geometric aliasing artifacts in other foveated rendering techniques. A set of perceptual user studies demonstrates the efficacy of our approach.

Type: Article
Title: Perceptual rasterization for head-mounted display image synthesis
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3306346
Publisher version: https://doi.org/10.1145/3306346
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10057126
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