Integrating low-level and high-level visual influences on eye movement behavior. Peters, R. J. & Itti, L. In Proc. Vision Science Society Annual Meeting (VSS07), May, 2007.
abstract   bibtex   
We propose a comprehensive computational framework unifying previous qualitative studies of high-level cognitive influences on eye movements with quantitative studies demonstrating the influence of low-level factors such as saliency. In this framework, a top-level "governor" uses high-level task information to determine how best to combine low-level saliency and gist-based task-relevance maps into a single eye-movement priority map. We recorded the eye movements of six trained subjects playing 18 different sessions of first-person perspective video games (car racing, flight combat, and "first-person shooter") and simultaneously recorded the game's video frames, giving about 18 hours of recording for 15,000,000 eye movement samples (240Hz) and 1.1TB of video data (640x480 pixels at 30Hz). We then computed measures of how well the individual saliency and task-relevance maps predicted observers' eye positions in each frame, and probed for the role of the governor in relationships between high-level task information -- such as altimeter and damage meter settings, or the presence/absence of a target -- and the predictive strength of the maps. One such relationship occurred in the flight combat game. In this game, observers are actively task-driven while tracking enemy planes, ignoring bottom-up saliency in favor of task-relevant items like the radar screen; then, after firing a missile, observers become passively stimulus-driven while awaiting visual confirmation of the missile hit. We confirmed this quantitatively by analyzing the correspondence between saliency and eye position across a window of +/-10s relative to the time of 328 such missile hits. Around -200ms (before the hit), the saliency correspondence begins to rise, reaching a peak at +100ms (after the hit) of 10-fold above the previous baseline, then is suppressed below baseline at +800ms, and rebounds back to baseline at +2000ms. Thus, one mechanism by which high-level cognitive information can influence eye movements is through dynamically weighting competing saliency and task-relevance maps.
@inproceedings{ Peters_Itti07vss,
  author = {R. J. Peters and L. Itti},
  title = {Integrating low-level and high-level visual influences on eye
                  movement behavior},
  abstract = {We propose a comprehensive computational framework unifying
                  previous qualitative studies of high-level cognitive
                  influences on eye movements with quantitative
                  studies demonstrating the influence of low-level
                  factors such as saliency. In this framework, a
                  top-level "governor" uses high-level task
                  information to determine how best to combine
                  low-level saliency and gist-based task-relevance
                  maps into a single eye-movement priority map.  We
                  recorded the eye movements of six trained subjects
                  playing 18 different sessions of first-person
                  perspective video games (car racing, flight combat,
                  and "first-person shooter") and simultaneously
                  recorded the game's video frames, giving about 18
                  hours of recording for 15,000,000 eye movement
                  samples (240Hz) and 1.1TB of video data (640x480
                  pixels at 30Hz). We then computed measures of how
                  well the individual saliency and task-relevance maps
                  predicted observers' eye positions in each frame,
                  and probed for the role of the governor in
                  relationships between high-level task information --
                  such as altimeter and damage meter settings, or the
                  presence/absence of a target -- and the predictive
                  strength of the maps.  One such relationship
                  occurred in the flight combat game. In this game,
                  observers are actively task-driven while tracking
                  enemy planes, ignoring bottom-up saliency in favor
                  of task-relevant items like the radar screen; then,
                  after firing a missile, observers become passively
                  stimulus-driven while awaiting visual confirmation
                  of the missile hit. We confirmed this quantitatively
                  by analyzing the correspondence between saliency and
                  eye position across a window of +/-10s relative to
                  the time of 328 such missile hits. Around -200ms
                  (before the hit), the saliency correspondence begins
                  to rise, reaching a peak at +100ms (after the hit)
                  of 10-fold above the previous baseline, then is
                  suppressed below baseline at +800ms, and rebounds
                  back to baseline at +2000ms. Thus, one mechanism by
                  which high-level cognitive information can influence
                  eye movements is through dynamically weighting
                  competing saliency and task-relevance maps.},
  booktitle = {Proc. Vision Science Society Annual Meeting (VSS07)},
  year = {2007},
  month = {May},
  type = {mod;bu;td;eye},
  review = {abs/conf}
}
Downloads: 0
About
Documentation
Keywords
Search
Users
Terms and Conditions of Use
Privacy Policy
Sitemap
© BibBase.org 2021