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A Gaze-Driven Evolutionary Algorithm to Study Aesthetic Evaluation of Visual Symmetry
Alexis D J Makin1, Marco Bertamini1, Andrew Jones1
1Psychological Sciences, University of Liverpool, Liverpool, UK.
I-Perception
|July 20, 2016
Summary
People prefer visual symmetry, but not always perfection. This study used a gaze-driven evolutionary algorithm to show that while explicit focus on symmetry increases it, general preference allows for some imperfection, with no effect of familiarity.
Area of Science:
- Psychology
- Computer Science
- Human-Computer Interaction
Background:
- Empirical evidence suggests a general human preference for visual symmetry.
- Understanding the nuances of aesthetic preferences, such as tolerance for imperfection, is crucial.
Purpose of the Study:
- To investigate automatic symmetry evaluation without explicit instruction.
- To determine if perfect symmetry or slight imperfection is preferred.
- To assess if familiarity diminishes symmetry preference.
Main Methods:
- Utilized a gaze-driven evolutionary algorithm with genes for symmetry (deviation-symmetry) and orientation.
- Employed eye-tracking technology to identify stimuli that captured and held observer attention.
- Tracked changes in gene distribution over 20 generations to quantify preference shifts.
Main Results:
- Explicitly seeking symmetry led to an increase in high-symmetry genes.
- Seeking preferred patterns resulted in a moderate increase in symmetry, indicating tolerance for imperfection.
- Free viewing and familiarity did not significantly alter symmetry preference or orientation.
Conclusions:
- The evolutionary algorithm approach provides a viable quantitative measure for aesthetic preferences.
- Human preference for symmetry is context-dependent, allowing for a degree of imperfection.
- Familiarity and orientation do not appear to be primary drivers of symmetry preference in this paradigm.
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