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

3DFace@Home：一项通过移动设备进行稳健且高精度面部 3D 重建的试点研究，用于家庭面部生长监测

• 批准号: EP/X036642/1
• 负责人: Ludovic Magerand
• 金额: $ 25.98万
• 依托单位: University of Dundee
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX036642%2F1
• 关键词: 3DFace; Home; pilot; study; robust

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.

3Dface@Home的目标是开发和测试一个系统，以在现实世界中最终用户的移动设备（例如家里的智能手机）在最终用户的移动设备中稳健地获得高度准确的面部3D重建。它是由移动应用程序制成的，使用户可以通过指导和有效性检查自己捕获其面部的图像。这些图像被发送到计算服务器，在该服务器中，将使用基于深度学习的面部3D重建嵌入多视图几何约束来获得面部的3D形状。该项目将旨在达到在影响面部生长的疾病的情况下测量解剖结构所需的次数准确性。将获取专门建造的数据集，包括面部畸形学的示例，并反映现实世界条件，该系统需要适应不良的照明，模糊图像或部分闭塞。将来，这项工作将有助于收集有关影响面部生长的疾病的遗传研究数据，并能够探索各种医疗领域的临床翻译。