Wei, W, Ho, ESL, McCay, KD, Damaševičius, R, Maskeliūnas, R and Esposito, A (2022) Assessing Facial Symmetry and Attractiveness using Augmented Reality. Pattern Analysis and Applications, 25 (3). pp. 635-651. ISSN 1433-7541
|
Published Version
Available under License Creative Commons Attribution. Download (1MB) | Preview |
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.
Impact and Reach
Statistics
Additional statistics for this dataset are available via IRStats2.