Development of Landmark-based Facial Asymmetry Evaluation

This paper presents a novel development of a real-time evaluation system for facial asymmetry. Using this tool, it is expected possibly to assess the severity of facial asymmetry based on local and global comparisons of facial components. While the local one measures distances between the landmarks inside each facial region, the global one focuses on the overall difference of all facial regions about the sagittal plane. This reported preliminary work is focused on assessing the suitability of the existing image landmark detection methods for a real-time evaluation. Three commonly used deep learning-based methodologies have been implemented and tested in order to identify robust facial landmark detection under various challenging conditions. It is hypothesized, that the proposed system will be able to provide a more accurate measurement of facial asymmetry. The key is the proposed use of the geodesic distance calculated based on the geometry of human faces, with the help of the state-of-art depth camera.