June 2006
Volume 6, Issue 6
Free
Vision Sciences Society Annual Meeting Abstract  |   June 2006
Learning gaze allocation priorities in complex environments
Author Affiliations
  • Jelena Jovancevic
    University of Rochester, Center for Visual Science
  • Brian Sullivan
    University of Rochester, Center for Visual Science
  • Mary Hayhoe
    University of Rochester, Center for Visual Science
Journal of Vision June 2006, Vol.6, 480. doi:10.1167/6.6.480
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      Jelena Jovancevic, Brian Sullivan, Mary Hayhoe; Learning gaze allocation priorities in complex environments. Journal of Vision 2006;6(6):480. doi: 10.1167/6.6.480.

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Abstract

In dynamic environments, gaze patterns are often driven by competing task goals, such as avoiding obstacles, controlling direction, etc. (Hayhoe and Ballard, TICS, 2005). How do observers determine gaze priorities, especially in uncertain environments? We investigated whether the history of experience with events in the environment influences the distribution of gaze. Subjects walked in a virtual environment where the probability of salient events could be manipulated. Subjects walked along a path with virtual pedestrians that could be triggered to walk on a collision path. Two groups of subjects were given experience (18 trials) either in a normal environment without colliding pedestrians, or in an environment with frequent potential collisions (approximately 1 per trial). Gaze distribution was measured for three objects types in the environment: normal pedestrians, colliders and other (i.e. fixations on the path or surroundings). The proportion of fixations that were on normal pedestrians was 23% without prior experience with colliding pedestrians, but rose to 31% if subjects had previous experience in a condition where there were frequent pedestrians on a collision path. Similarly, when colliders were present, subjects devoted fewer fixations to normal pedestrians if they had prior experience without colliders (29% vs. 35%). This result suggests that subjects use their experience with relevant events to adjust gaze priorities in situations when there are multiple task goals. This is consistent with predictions of computational models of attentional allocation while walking (Rothkopf and Ballard, VSS, 2005).

Jovancevic, J. Sullivan, B. Hayhoe, M. (2006). Learning gaze allocation priorities in complex environments [Abstract]. Journal of Vision, 6(6):480, 480a, http://journalofvision.org/6/6/480/, doi:10.1167/6.6.480. [CrossRef]
Footnotes
 Supported by NIH grants: EY-05729 and RR-09283
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