Abstract
Shape and size are two important visual channels that underpin our ability to reason about the visual world in settings ranging from natural scenes to informational charts and diagrams. Strong evidence in the vision science (Makovski, 2017) and data visualization (Smart & Szafir, 2019) literature suggests that shape and size perception are inextricably linked to each other, with asymmetric influences of either channel upon the other. To better understand these influences and begin exploring the visual features that contribute to them, we designed an experiment to address the following question: “how do people judge the size of simple 2D shapes varying in geometric properties at multiple scales?” We asked 82 subjects on Amazon Mechanical Turk to adjust different target shapes until they appeared the same size as an array of homogeneous background shapes, and collected response data on combinations of representative filled, unfilled, and open shape categories at three levels of size. We analyzed the delta between target and background shape size judgments using a generalized linear model, and found statistical significance for the role of size, target and distractor features, and the interaction of shape and size (all with P < .001). As shape size increased, the delta between target and background shapes decreased. In medium and large conditions, open shapes needed to be made smaller to appear the same size as filled or unfilled shapes, lending support to the open-object illusion. These findings have practical and theoretical implications. Visualization tools and designers would benefit from sets of symbols normalized for perceptual size at different scales; future studies can explore more situated tasks and contexts to that end. Furthermore, theories underlying shape perception should account for characteristics such as visual density, geometric properties, and contour closure, as these features produced significant differences in perceived size in this study.