June 2006
Volume 6, Issue 6
Vision Sciences Society Annual Meeting Abstract  |   June 2006
Examining the factors that influence change detection
Author Affiliations
  • Daniel J. Simons
    University of Illinois
  • Michael S. Ambinder
    University of Illinois
  • Xiaoang Irene Wan
    University of Illinois
  • Gabriel Nevarez
    Cardiff University
  • Eamon Caddigan
    University of Illinois
Journal of Vision June 2006, Vol.6, 56. doi:https://doi.org/10.1167/6.6.56
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      Daniel J. Simons, Michael S. Ambinder, Xiaoang Irene Wan, Gabriel Nevarez, Eamon Caddigan; Examining the factors that influence change detection. Journal of Vision 2006;6(6):56. doi: https://doi.org/10.1167/6.6.56.

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

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A core conclusion from the change blindness literature is that change detection is enhanced when attention is exogenously cued to the change region (Scholl, 2000) or when attention is directed to the changed region due to its perceived salience (Wright, 2005) or semantic importance (Rensink et al, 1997). Most studies have examined the contribution of only one such factor, typically with a single change detection task and relatively few images. We explored the factors that predict change detection using a large set of images, multiple tasks (flicker, one-shot, etc), and both judged and image-based measures of importance, salience, and magnitude.

Judged salience predicted change detection performance, even after controlling for semantic centrality. Yet, semantic centrality made little contribution to detection performance after accounting for judged salience, suggesting that center-of-interest effects might be driven by image salience. However, salience judgments were only minimally correlated with the results of an automated salience analysis, suggesting that factors other than image salience contributed to judged salience. Interestingly, image-based salience of the original but not the changed image predicted change detection performance in the one-shot task. Image-based salience had less predictive value for the flicker task, suggesting the use of different attentional strategies in performing these tasks. We consider the implications of a variety of measures of change magnitude and centrality for the generalizability of inferences about the mechanisms of change detection across images and tasks.

Simons, D. J. Ambinder, M. S. Wan, X. I. Nevarez, G. Caddigan, E. (2006). Examining the factors that influence change detection [Abstract]. Journal of Vision, 6(6):56, 56a, http://journalofvision.org/6/6/56/, doi:10.1167/6.6.56. [CrossRef]

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