Purchase this article with an account.
Amelia C. Warden, Jessica K. Witt, Mengzhu Fu, Michael Dodd; Overestimation of Variability in Ensembles of Line Orientation, Size, and Hue. Journal of Vision 2020;20(11):1240. doi: https://doi.org/10.1167/jov.20.11.1240.
Download citation file:
© ARVO (1962-2015); The Authors (2016-present)
Ensemble perception utilizes our visual system's natural abilities to extract summary statistics from sets of similar objects. Our perceptual system can accurately detect the mean of these ensembles. However, previous research has shown that our visual system is biased to overestimate variability. This bias to overestimate variability was stronger when the objects were more similar to each other. This prior research concerned variability of line orientations. We extended this work to explore whether this overestimation bias is a general phenomenon and therefore applies to other visual features as well. Using the method of adjustment, participants made judgments about the variability of line orientation, size, and hue in sets of ensembles (lines and circles). Participants viewed 9 target circles of various sizes presented one-at-a-time, then adjusted the sizes of five comparison circles presented simultaneously to match the variability in the target display. A similar task was used to assess how participants estimated variability in line orientation and hue. Participants overestimated variability, and this was true for all 3 features. Moreover, participants overestimated variability to a greater extent when there was less variability in the display for circle size (95% overestimation), line orientation (51% overestimation), and hue (155% overestimation) compared to high levels of variability (-11%, -10%, -3%, respectively). Understanding how we perceive variability in ensembles is essential when making judgments about critical information in medical images. For instance, how distributed calcifications are within a mammogram informs whether a radiologist diagnoses a patient with cancer. Further research will attempt to elucidate the mechanisms of ensemble perceptual and test the robustness of the bias to overestimate variability.
This PDF is available to Subscribers Only