High-speed visual estimation using preattentive processing


Journal article


C. G. Healey, K. S. Booth, J. T. Enns
ACM Transactions on Computer Human Interaction, vol. 3(2), 1996, pp. 107-135

View PDF Semantic Scholar DBLP DOI
Cite

Cite

APA   Click to copy
Healey, C. G., Booth, K. S., & Enns, J. T. (1996). High-speed visual estimation using preattentive processing. ACM Transactions on Computer Human Interaction, 3(2), 107–135.


Chicago/Turabian   Click to copy
Healey, C. G., K. S. Booth, and J. T. Enns. “High-Speed Visual Estimation Using Preattentive Processing.” ACM Transactions on Computer Human Interaction 3, no. 2 (1996): 107–135.


MLA   Click to copy
Healey, C. G., et al. “High-Speed Visual Estimation Using Preattentive Processing.” ACM Transactions on Computer Human Interaction, vol. 3, no. 2, 1996, pp. 107–35.


BibTeX   Click to copy

@article{c1996a,
  title = {High-speed visual estimation using preattentive processing},
  year = {1996},
  issue = {2},
  journal = {ACM Transactions on Computer Human Interaction},
  pages = {107-135},
  volume = {3},
  author = {Healey, C. G. and Booth, K. S. and Enns, J. T.}
}

Abstract

A new method is presented for performing rapid and accurate numerical estimation. The method is derived from an area of human cognitive psychology called preattentive processing. Preattentive processing refers to an initial organization of the visual field based on cognitive operations believed to be rapid, automatic, and spatially parallel. Examples of visual features that can be detected in this way include hue, intensity, orientation, size, and motion. We beleive that studies from preattentive vision should be used to assist in the design of visualization tools, especially those for which high-speed target detection, boundary identification, and region detection are important. In our present study, we investigated two known preattentive features (hue and orientation) in the context of a new task (numerical estimation) in order to see whether preattentive estimation was possible. Our experiments tested displays that were designed to visualize data from salmon migration simulations. The results showed that rapid and accurate estimation was indeed possible using either hue or orientation. Furthermore, random variation in one of these features resulted in no interference when subjects estimated the percentage of the other. To test the generality of our results, we varied two important display parameters—display duration and feature difference—and found boundary conditions for each. Implications of our results for application to real-world data and tasks are discussed.


Share



Follow this website


You need to create an Owlstown account to follow this website.


Sign up

Already an Owlstown member?

Log in