Storey, Gary and Bouridane, Ahmed and Jiang, Richard and Li, Chang-Tsun (2020) Atypical Facial Landmark Localisation with Stacked Hourglass Networks:A Study on 3D Facial Modelling for Medical Diagnosis. In: Deep Biometrics. Unsupervised and Semi-Supervised Learning . Springer, Cham, pp. 37-49. ISBN 9783030325824
Full text not available from this repository.Abstract
While facial biometrics has been widely used for identification purpose, it has recently been researched as medical biometrics for a range of diseases. In this chapter, we investigate the facial landmark detection for atypical 3D facial modelling in facial palsy cases, while potentially such modelling can assist the medical diagnosis using atypical facial features. In our work, a study of landmarks localisation methods such as stacked hourglass networks is conducted and evaluated to ascertain their accuracy when presented with unseen atypical faces. The evaluation highlights that the state-of-the-art stacked hourglass architecture outperforms other traditional methods.