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The Visual Turing Test is the ultimate goal to evaluate the realism of holographic displays. Previous studies have focused on addressing challenges such as limited e ́tendue and image quality over a large focal volume, but they have not investigated the effect of pupil sampling on the viewing experience in full 3D holograms. In this work, we tackle this problem with a novel hologram generation algorithm motivated by matching the projection operators of incoherent (Light Field) and coherent (Wigner Function) light transport. To this end, we supervise hologram computation using synthesized photographs, which are rendered on-the-fly using Light Field refocusing from stochastically sampled pupil states during optimization. The proposed method produces holograms with correct parallax and focus cues, which are important for passing the Visual Turing Test. We validate that our approach compares favorably to state-of-the-art CGH algorithms that use Light Field and Focal Stack supervision. Our experiments demonstrate that our algorithm improves the viewing experience when evaluated under a large variety of different pupil states. 

Display power consumption is an emerging concern for untethered devices. This goes double for augmented and virtual extended reality (XR) displays, which target high refresh rates and high resolutions while conforming to an ergonomically light form factor. A number of image mapping techniques have been proposed to extend battery usage. However, there is currently no comprehensive quantitative understanding of how the power savings provided by these methods compare to their impact on visual quality. We set out to answer this question. To this end, we present a perceptual evaluation of algorithms (PEA) for power optimization in XR displays (PODs). Consolidating a portfolio of six power-saving display mapping approaches, we begin by performing a large-scale perceptual study to understand the impact of each method on perceived quality in the wild. This results in a unified quality score for each technique, scaled in just-objectionable-difference (JOD) units. In parallel, each technique is analyzed using hardware-accurate power models. The resulting JOD-to-Milliwatt transfer function provides a first-of-its-kind look into tradeoffs offered by display mapping techniques, and can be directly employed to make architectural decisions for power budgets on XR displays. Finally, we leverage our study data and power models to address important display power applications like the choice of display primary, power implications of eye tracking, and more¹. 

Holographic displays promise to deliver unprecedented display capabilities in augmented reality applications, featuring a wide field of view, wide color gamut, spatial resolution, and depth cues all in a compact form factor. While emerging holographic display approaches have been successful in achieving large étendue and high image quality as seen by a camera, the large étendue also reveals a problem that makes existing displays impractical: the sampling of the holographic field by the eye pupil. Existing methods have not investigated this issue due to the lack of displays with large enough étendue, and, as such, they suffer from severe artifacts with varying eye pupil size and location. We show that the holographic field as sampled by the eye pupil is highly varying for existing display setups, and we propose pupil-aware holography that maximizes the perceptual image quality irrespective of the size, location, and orientation of the eye pupil in a near-eye holographic display. We validate the proposed approach both in simulations and on a prototype holographic display and show that our method eliminates severe artifacts and significantly outperforms existing approaches.