Hyeonseung Yu1,
Mojtaba Bemana1,
Marek Wernikowski2,
Michał Chwesiuk2,
Okan Tarhan Tursun1,
Gurprit Singh1,
Karol Myszkowski1,
Radosław Mantiuk2,
Hans-Peter Seidel1,
Piotr Didyk1,3
1Max Planck Institute for Informatics, Saarbrücken
2West Pomeranian University of Technology, Szczecin
3Universit della Svizzera italiana, Lugano
In IEEE VR 2019 (Conference on Virtual Reality and 3D User Interfaces)
We build a two-plane VR display to test the rendering strategy. The
schematic and photograph of the setup are shown (BS:Beam splitter, ET:Eye tracker). For
each eye, images from two 2560 × 1440 LCD displays (Topfoison
TF60010A) are combined with a beam splitter (Edmund Optics #64-
408) and magnified with an achromatic lens (Thorlabs AC508-080-A).
Eye-trackers (Pupil Labs) are placed right behind the two lenses. The
optical system for the right eye is mounted on the linear stage for
adjusting the interpupillar distance. The dioptric distances to the front
and back virtual planes are set to 2.0 D and 1.4 D, respectively
Abstract
Multi-focal plane and multi-layered light-field displays are promising solutions for addressing all visual cues observed
in the real world. Unfortunately, these devices usually require expensive optimizations to compute a suitable decomposition of the
input light field or focal stack to drive individual display layers. Although these methods provide near-correct image reconstruction, a
significant computational cost prevents real-time applications. A simple alternative is a linear blending strategy which decomposes a
single 2D image using depth information. This method provides real-time performance, but it generates inaccurate results at occlusion
boundaries and on glossy surfaces. This paper proposes a perception-based hybrid decomposition technique which combines the
advantages of the above strategies and achieves both real-time performance and high-fidelity results. The fundamental idea is to apply
expensive optimizations only in regions where it is perceptually superior, e.g., depth discontinuities at the fovea, and fall back to less
costly linear blending otherwise. We present a complete, perception-informed analysis and model that locally determine which of the
two strategies should be applied. The prediction is later utilized by our new synthesis method which performs the image decomposition.
The results are analyzed and validated in user experiments on a custom multi-plane display.
