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DTSTART:18871231T000000
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BEGIN:VEVENT
DTSTAMP:20230103T035309Z
LOCATION:Room 324\, Level 3\, West Wing
DTSTART;TZID=Asia/Seoul:20221207T153000
DTEND;TZID=Asia/Seoul:20221207T170000
UID:siggraphasia_SIGGRAPH Asia 2022_sess160_papers_307@linklings.com
SUMMARY:Color-Perception-Guided Display Power Reduction for Virtual Realit
 y
DESCRIPTION:Technical Communications, Technical Papers\n\nColor-Perception
 -Guided Display Power Reduction for Virtual Reality\n\nDuinkharjav, Chen, 
 Tyagi, He, Zhu...\n\nBattery life is an increasingly urgent challenge for 
 today's untethered VR and AR devices. However, the power efficiency of hea
 d-mounted displays is naturally at odds with growing computational require
 ments driven by better resolution, refresh rate, and dynamic ranges, all o
 f which reduce the sustained usage time of untethered AR/VR devices. For i
 nstance, the Oculus Quest 2, under a fully-charged battery, can sustain on
 ly 2 to 3 hours of operation time. Prior display power reduction technique
 s mostly target smartphone displays. Directly applying smartphone display 
 power reduction techniques, however, degrades the visual perception in AR/
 VR with noticeable artifacts. For instance, the "power-saving mode" on sma
 rtphones uniformly lowers the pixel luminance across the display and, as a
  result, presents an overall darkened visual perception to users if direct
 ly applied to VR content.\n\nOur key insight is that VR display power redu
 ction must be cognizant of the gaze-contingent nature of high field-of-vie
 w VR displays. To that end, we present a gaze-contingent system that, with
 out degrading luminance, minimizes the display power consumption while pre
 serving high visual fidelity when users actively view immersive video sequ
 ences. This is enabled by constructing 1) a gaze-contingent color discrimi
 nation model through psychophysical studies, and 2) a display power model 
 (with respect to pixel color) through real-device measurements. Critically
 , due to the careful design decisions made in constructing the two models,
  our algorithm is cast as a constrained optimization problem with a closed
 -form solution, which can be implemented as a real-time, image-space shade
 r. We evaluate our system using a series of psychophysical studies and lar
 ge-scale analyses on natural images. Experiment results show that our syst
 em reduces the display power by as much as 24% (14% on average) with littl
 e to no perceptual fidelity degradation.\n\nRegistration Category: FULL AC
 CESS, ON-DEMAND ACCESS\n\nLanguage: ENGLISH\n\nFormat: IN-PERSON, ON-DEMAN
 D
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_307&sess=sess16
 0
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