Quantification of interface visual complexity

Miniukovich, Aliaksei and De angeli, Antonella (2014) Quantification of interface visual complexity. In: 2014 International Working Conference on Advanced Visual Interfaces, 27-29 May 2014, Como, Italy.

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive


Designers strive for enjoyable user experience (UX) and put a significant effort into making graphical user interfaces (GUI) both usable and beautiful. Our goal is to minimize their effort: with this purpose in mind, we have been studying automatic metrics of GUI qualities. These metrics could enable designers to iterate their designs more quickly. We started from the psychological findings that people tend to prefer simpler things. We then assumed visual complexity determinants also determine visual aesthetics and outlined eight of them as belonging to three dimensions: information amount (visual clutter and color variability), information organization (symmetry, grid, ease-of-grouping and prototypicality), and information discriminability (contour density and figure-ground contrast). We investigated five determinants (visual clutter, symmetry, contour density, figure-ground contrast and color variability) and proposed six associated automatic metrics. These metrics take screenshots of GUI as input and can thus be applied to any type of GUI. We validated the metrics through a user study: we gathered the ratings of immediate impressions of GUI visual complexity and aesthetics, and correlated them with the output of the metrics. The output explained up to 51 of aesthetics ratings and 50 of complexity ratings. This promising result could be further extended towards the creation of tLight, our automatic GUI evaluation tool.

Keywords:Clutter (information theory), Design, Color variability, Graphical user interfaces (GUI), immediate impression, Information amount, Information organization, metric validation, User experiences (ux), Visual Aesthetics, Graphical user interfaces
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
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ID Code:25475
Deposited On:14 Aug 2017 09:39

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