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Polygon-Based Drawing Accuracy Analysis and Positive/Negative Space

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The study of drawing generally depends on ratings by human critics and self-reported expertise of the drawers. To complement those approaches, we developed an objective continuous performance-based measure of drawing accuracy. This measure represents drawings as sets of landmark points and analyses features of particular research interest by comparing polygons of those features’ landmark points with their counterpart polygons in a veridical image. This approach produces local accuracy measures (for each polygon), a global accuracy measure (the mean across several polygons), and four distinct properties of a polygon for analysis: its size, its position, its orientation and the proportionality of its shape. We briefly describe the method and its potential research applications in drawing education and visual perception, then apply it to a specific research question: Are we more accurate when drawing in the so-called ‘positive space’ (or figure)? In a polygon-based accuracy analysis of 34 representational drawings, expert drawers outperformed less experienced participants on overall accuracy and every dimension of polygon error. Comparing polygons in the positive and negative space revealed an apparent trade-off on the different dimensions of polygon error. People were more accurate at proportionality and position in the positive space than in the negative space, but more accurate at orientation in the negative space. The contribution is the use of an objective, performance-based analysis of geometric deformations to study the accuracy of drawings at different levels of organization, here, in the positive and negative space.

Affiliations: 1: 1University of Waterloo, Ontario, Canada; 2: 2Stanford University, California, USA


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