Introduction: The current literature on facial attractiveness focuses on anterior-posterior facial portraits, with lateral facial analysis limited to comparing facial attractiveness scores with various facial measurements. Here we use a novel approach to more rigorously study lateral facial attractiveness by combining morphing software and a genetic algorithm with web-based facial attractiveness scoring to evolve attractive lateral facial images.
Objective: The objectives of this study were to: 1) identify the key lateral facial landmarks that produce realistic lateral facial images; and 2) determine if a genetic algorithm combined with morphing software can progressively evolve lateral facial attractiveness.
Methods: A cohort of lateral facial portraits were selectively paired by a genetic algorithm biased towards more attractive faces, and "bred" with morphing software to create a cohort of faces more attractive than the original. By repeating this process facial attractiveness was "evolved" through several cohorts.
Results: Key facial landmarks are: trichion to glabella, nasion to tip of nose, subnasale to labrale inferius, and pogonion to menton. Facial attractiveness scores increased in each successive cohort.
Conclusion: Using these landmarks and methodologies, realistic lateral facial portraits were created and progressively increased in facial attractiveness. This technique is a robust alternative to traditional approaches in the analysis of lateral facial attractiveness.