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DTSTAMP:20260114T163703Z
LOCATION:Meeting Room C4.9+C4.10\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231213T165000
DTEND;TZID=Australia/Melbourne:20231213T170500
UID:siggraphasia_SIGGRAPH Asia 2023_sess126_papers_282@linklings.com
SUMMARY:The Shortest Route Is Not Always the Fastest: Probability-Modeled 
 Stereoscopic Eye Movement Completion Time in VR
DESCRIPTION:Budmonde Duinkharjav and Benjamin Liang (New York University),
  Anjul Patney and Rachel Brown (NVIDIA Research), and Qi Sun (New York Uni
 versity)\n\nSpeed and consistency of target-shifting play a crucial role i
 n human ability to perform complex tasks. Shifting our gaze between object
 s of interest quickly and consistently requires changes both in depth and 
 direction. Gaze changes in depth are driven by slow, inconsistent vergence
  movements which rotate the eyes in opposite directions, while changes in 
 direction are driven by ballistic, consistent movements called saccades, w
 hich rotate the eyes in the same direction. In the natural world, most of 
 our eye movements are a combination of both types. While scientific consen
 sus on the nature of saccades exists, vergence and combined movements rema
 in less understood and agreed upon.\n\nWe eschew the lack of scientific co
 nsensus in favor of proposing an operationalized computational model which
  predicts the speed of any type of gaze movement during target-shifting in
  3D. To this end, we conduct a psychophysical study in a stereo VR environ
 ment to collect more than 12,000 gaze movement trials, analyze the tempora
 l distribution of the observed gaze movements, and fit a probabilistic mod
 el to the data. We perform a series of objective measurements and user stu
 dies to validate the model. The results demonstrate its predictive accurac
 y, generalization, as well as applications for optimizing visual performan
 ce by altering content placement. Lastly, we leverage the model to measure
  differences in human target-changing time relative to the natural world, 
 as well as suggest scene-aware projection depth. By incorporating the comp
 lexities and randomness of human oculomotor control, we hope this research
  will support new behavior-aware metrics for VR/AR display design, interfa
 ce layout, and gaze-contingent rendering.\n\nRegistration Category: Full A
 ccess\n\nSession Chair: Jin Ryong Kim (TBU)\n\n
URL:https://asia.siggraph.org/2023/full-program?id=papers_282&sess=sess126
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