Modeling visual search on a rough surface

Alasdair D. F. Clarke*, Mike J. Chantler, Patrick R. Green

*Corresponding author for this work

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

The LNL (linear, non-linear, linear) model has previously been successfully applied to the problem of texture segmentation. In this study we investigate the extent to which a simple LNL model can simulate human performance in a search task involving a target on a textured surface. Two different classes of surface are considered: 1/f(beta)-noise and near-regular textures. We find that in both cases the search performance of the model does not differ significantly from that of people, over a wide range of task difficulties.

Original languageEnglish
Article number11
Number of pages12
JournalJournal of Vision
Volume9
Issue number4
DOIs
Publication statusPublished - 13 Apr 2009

Keywords

  • linear-nonlinear-linear model
  • visual search
  • texture
  • texture analysis
  • Saccadic selectivity
  • computational model
  • eye-movements
  • direction
  • vision
  • target

Cite this

Clarke, A. D. F., Chantler, M. J., & Green, P. R. (2009). Modeling visual search on a rough surface. Journal of Vision, 9(4), [11]. https://doi.org/10.1167/9.4.11