August 2012
Volume 12, Issue 9
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2012
Effects of flow field noise and density on optic flow parsing
Author Affiliations
  • Andrew Foulkes
    School of Psychological Science, Manchester University, UK
  • Simon Rushton
    School of Psychology, Cardiff University, UK
  • Paul Warren
    School of Psychological Science, Manchester University, UK
Journal of Vision August 2012, Vol.12, 235. doi:10.1167/12.9.235
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      Andrew Foulkes, Simon Rushton, Paul Warren; Effects of flow field noise and density on optic flow parsing. Journal of Vision 2012;12(9):235. doi: 10.1167/12.9.235.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

We have previously suggested that neural flow parsing mechanisms, which subtract global optic flow consistent with observer movement, play a role in recovery of scene-relative object movement. In this study, we investigate how the quality (noise) and amount (density) of information in the optic flow field (OFF) affect flow parsing. We predict that since flow parsing involves global motion processing it should be relatively robust to noise and density manipulations.

Participants fixated at the centre of a radial flow field of limited lifetime dots, and were asked to judge the direction of motion of a laterally displaced probe moving vertically upwards. To limit the contribution of local motion processing mechanisms, no flow field dots were presented in a patch of radius 3 deg centred on the probe. The 2D motion directions of the dots were subject to three levels of zero mean additive Gaussian noise (s.d. = 0, 7.5, or 15 degrees). We also varied the density of the OFF by changing the instantaneous number of dots on screen (5, 50, 100, 200 dots). We measured the relative tilt of the probe (the angular difference between the physical probe direction and the perceived direction).

Analyses revealed a relatively small (although significant) decrease in the magnitude of the realative tilt effect with the increased noise (on the order of 10-20%). With respect to the density manipulation, although the relative tilt effect was significantly reduced in the lowest density condition, it was stable over all other dot densities. These data suggest that, as anticipated, flow parsing is relatively robust to variations in noise and density. The data are broadly in line with results for heading recovery when noise and density are manipulated. This provides some evidence that flow parsing and heading recovery share common mechanisms.

Meeting abstract presented at VSS 2012

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