Assessing Facial Symmetry and Attractiveness using Augmented Reality

Wei Wei, Edmond S. L. Ho, Kevin McCay, Robertas Damaševičius*, Rytis Maskeliūnas, Anna Esposito

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)
86 Downloads (Pure)

Abstract

Facial symmetry is a key component in quantifying the perception of beauty. In this paper, we propose a set of facial features computed from facial landmarks which can be extracted at a low computational cost. We quantitatively evaluated the proposed features for predicting perceived attractiveness from human portraits on four benchmark datasets (SCUT-FBP, SCUT-FBP5500, FACES and Chicago Face Database). Experimental results showed that the performance of the proposed features is comparable to those extracted from a set with much denser facial landmarks. The computation of facial features was also implemented as an augmented reality (AR) app developed on Android OS. The app overlays four types of measurements and guidelines over a live video stream, while the facial measurements are computed from the tracked facial landmarks at run time. The developed app can be used to assist plastic surgeons in assessing facial symmetry when planning reconstructive facial surgeries.

Original languageEnglish
Pages (from-to)635–651
Number of pages27
JournalPattern Analysis and Applications
Volume25
Issue number3
Early online date28 Mar 2021
DOIs
Publication statusPublished - 1 Aug 2022

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