3DFace@Home: A pilot study for robust and highly accurate facial 3D reconstruction from mobile devices for facial growth monitoring at home

The goal of 3Dface@Home is to develop and test a system to robustly obtain highly accurate facial 3D reconstruction from end users' mobile devices in real world conditions, such as one's smartphone at home. It is made of a mobile application allowing the user to capture images of their face by themselves with guidance and validity check. Those images are sent to a computational server where a deep learning based facial 3D reconstruction embedding multi-view geometry constraints will be used to obtain the 3D shape of the face. The project will aim to reach sub-millimetre accuracy required for measuring anatomical structures in the context of disease affecting facial growth. A purpose-built dataset will be acquired, including examples of facial dysmorphology, and reflecting real world conditions the system needs to be robust to such as bad illumination, blurry images or partial occlusion. In the future, this work will facilitate mass collection of data for genetic studies on disease affecting facial growth and enable the exploration of clinical translation in a variety of medical fields.