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BEGIN:VEVENT
DTSTAMP:20230103T035306Z
LOCATION:Auditorium\, Level 5\, West Wing
DTSTART;TZID=Asia/Seoul:20221206T100000
DTEND;TZID=Asia/Seoul:20221206T120000
UID:siggraphasia_SIGGRAPH Asia 2022_sess153_papers_307@linklings.com
SUMMARY:Color-Perception-Guided Display Power Reduction for Virtual Realit
 y
DESCRIPTION:Technical Papers\n\nColor-Perception-Guided Display Power Redu
 ction for Virtual Reality\n\nDuinkharjav, Chen, Tyagi, He, Zhu...\n\nBatte
 ry life is an increasingly urgent challenge for today's untethered VR and 
 AR devices. However, the power efficiency of head-mounted displays is natu
 rally at odds with growing computational requirements driven by better res
 olution, refresh rate, and dynamic ranges, all of which reduce the sustain
 ed usage time of untethered AR/VR devices. For instance, the Oculus Quest 
 2, under a fully-charged battery, can sustain only 2 to 3 hours of operati
 on time. Prior display power reduction techniques mostly target smartphone
  displays. Directly applying smartphone display power reduction techniques
 , however, degrades the visual perception in AR/VR with noticeable artifac
 ts. For instance, the "power-saving mode" on smartphones uniformly lowers 
 the pixel luminance across the display and, as a result, presents an overa
 ll darkened visual perception to users if directly applied to VR content.\
 n\nOur key insight is that VR display power reduction must be cognizant of
  the gaze-contingent nature of high field-of-view VR displays. To that end
 , we present a gaze-contingent system that, without degrading luminance, m
 inimizes the display power consumption while preserving high visual fideli
 ty when users actively view immersive video sequences. This is enabled by 
 constructing 1) a gaze-contingent color discrimination model through psych
 ophysical studies, and 2) a display power model (with respect to pixel col
 or) through real-device measurements. Critically, due to the careful desig
 n 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 shader. We evaluate our system 
 using a series of psychophysical studies and large-scale analyses on natur
 al images. Experiment results show that our system reduces the display pow
 er by as much as 24% (14% on average) with little to no perceptual fidelit
 y degradation.\n\nRegistration Category: FULL ACCESS, EXPERIENCE PLUS ACCE
 SS, EXPERIENCE ACCESS, TRADE EXHIBITOR\n\nLanguage: ENGLISH\n\nFormat: IN-
 PERSON
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_307&sess=sess15
 3
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