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

3Dface@Home的目标是开发和测试一个系统，以便在真实的世界条件下从最终用户的移动的设备（例如家中的智能手机）稳健地获得高度准确的面部3D重建。它是由一个移动的应用程序，允许用户捕捉自己的脸与指导和有效性检查的图像。这些图像被发送到计算服务器，其中基于深度学习的嵌入多视图几何约束的面部3D重建将用于获得面部的3D形状。该项目的目标是达到在影响面部生长的疾病背景下测量解剖结构所需的亚毫米精度。将获得一个专门构建的数据集，包括面部畸形的例子，并反映系统需要鲁棒的真实的世界条件，如不良照明，模糊图像或部分遮挡。未来，这项工作将促进影响面部生长的疾病的遗传学研究的大规模数据收集，并使各种医学领域的临床翻译探索成为可能。

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.