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

6 Citations (Scopus)
62 Downloads (Pure)


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 our 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 our 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 guide lines 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
Number of pages27
JournalPattern Analysis and Applications
Early online date28 Mar 2021
Publication statusE-pub ahead of print - 28 Mar 2021


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