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DTSTAMP:20250110T023313Z
LOCATION:Hall B5 (1)\, B Block\, Level 5
DTSTART;TZID=Asia/Tokyo:20241206T151300
DTEND;TZID=Asia/Tokyo:20241206T152700
UID:siggraphasia_SIGGRAPH Asia 2024_sess148_papers_489@linklings.com
SUMMARY:Identifying Behavioral Correlates to Visual Discomfort
DESCRIPTION:Technical Papers\n\nDavid Tovar (Reality Labs, Meta; Vanderbil
 t University); James Wilmott and Xiuyun Wu (Reality Labs, Meta); Daniel Ma
 rtin (Reality Labs Research, Meta; Universidad de Zaragoza); and Michael P
 roulx, Dave Lindberg, Yang Zhao, Olivier Mercier, and Phillip Guan (Realit
 y Labs Research, Meta)\n\nOutside of self-report surveys, there are no pro
 ven, reliable methods to quantify visual discomfort or visually induced mo
 tion sickness symptoms when using head-mounted displays. While valuable to
 ols, self-report surveys suffer from potential biases and low sensitivity 
 due to variability in how respondents may assess and report their experien
 ce. Consequently, extreme visual-vestibular conflicts are generally used t
 o induce discomfort symptoms large enough to measure reliably with surveys
  (e.g., stationary participants riding virtual roller coasters). An emergi
 ng area of research is the prediction of discomfort survey results from ph
 ysiological and behavioral markers. However, the signals derived from expe
 riences that are explicitly designed to be uncomfortable may not generaliz
 e to more naturalistic experiences where comfort is prioritized. In this w
 ork we introduce a custom VR headset designed to introduce significant nea
 r-eye optical distortion (i.e., pupil swim) to induce visual discomfort du
 ring more typical VR experiences. We evaluate visual comfort in our headse
 t while users play the popular VR title Job Simulator and show that eye-tr
 acked dynamic distortion correction improves visual comfort in a multi-ses
 sion, within-subjects user study. We additionally use representational sim
 ilarity analysis to highlight changes in head and gaze behavior that are p
 otentially more sensitive to visual discomfort than surveys.\n\nRegistrati
 on Category: Full Access, Full Access Supporter\n\nLanguage Format: Englis
 h Language\n\nSession Chair: Peng Song (Singapore University of Technology
  and Design (SUTD))
URL:https://asia.siggraph.org/2024/program/?id=papers_489&sess=sess148
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