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Related Experiment Videos

Effects of 'local' clutter on human target detection.

Gary J Ewing1, Christopher J Woodruff, Douglas Vickers

  • 1Command and Control Division, Defence Science and Technology Organisation, Edinburgh SA, Australia. gary.ewing@dsto.defence.gov.au

Spatial Vision
|January 18, 2006
PubMed
Summary

The size of the local clutter region significantly impacts target detection probability. This effect is more pronounced for smaller targets and depends on clutter characteristics, not just arbitrary region sizes.

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Area of Science:

  • Visual perception
  • Computational modeling
  • Image analysis

Background:

  • Clutter properties are theoretically defined globally or locally.
  • Current literature lacks justification for arbitrary local clutter domain sizes (e.g., twice the target size).
  • This arbitrary approach may affect the accuracy of clutter metrics.

Purpose of the Study:

  • To investigate the impact of local clutter region size on target detection probability.
  • To challenge the arbitrary definition of local clutter domains in existing literature.
  • To develop a model explaining the relationship between clutter characteristics and detection performance.

Main Methods:

  • Analysis of target detection probability under varying local clutter region sizes.
  • Comparison of clutter effects on targets of different visual angles (<0.8 degrees vs. larger).

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  • Development of a simple model based on clutter auto-covariance functions.

    • Main Results:

    • Local clutter region size strongly influences target detection probability.
    • Detection probability is affected by clutter regions significantly larger than twice the target size.
    • Smaller targets (<0.8 degrees visual angle) exhibit a quadratic fall-off in performance with increasing clutter region size, while larger targets show a linear fall-off.
    • The auto-covariance function of clutter is a key determinant of the effective local clutter region size.

    Conclusions:

    • The definition of local clutter domains requires re-evaluation beyond arbitrary multiples of target size.
    • Human visual performance in cluttered environments is sensitive to the spatial extent and characteristics of the clutter.
    • A model based on clutter auto-covariance offers a more principled approach to defining local clutter effects.