SGER: Developing a high-definition face modeling system for recognition and generation of face and face expressions

人脸分析与合成在人机交互、安全、娱乐等领域的应用已经成为科学界和工业界不竭的研究课题。用于识别或动画的最先进的3D面部模型不能表示和识别面部外观或特征配置的细微差异，这是在个体之间进行唯一区分所必需的。在这个项目中，PI将开发一种新的技术，用于在比目前可能实现的更高的细节水平上分析和合成人脸。提出了一种用于标记和建模的所谓三维地形表示法，其中人脸由基于曲面曲率和地形标记的可变分辨率的活动网格表示。PI期望在多个尺度上追踪某些特征的行为将揭示有关潜在物理过程本质的宝贵信息，从而建立面部特征与表面属性（即峰、坑、脊、沟、鞍、山、平等）之间的内在关系。反过来，这将以直观和详细的方式提供对面部外观和表现如何随表情变化而变化的科学理解，并将为3D面部表面如何包含2D平面图像中未显示的嵌入式特征提供深刻的新见解。PI预计，这项试点研究最终将使他能够开发出一种“人性化”系统，用于识别人脸及其表情（甚至情绪），以及一种自动生成逼真面部表情的系统。更广泛的影响：这项研究将提高我们对人类视觉认知过程的理解，并影响下一代人机界面的发展，使机器能够识别面部表情。这项工作还将在执法（面部照片搜索、安全监控和测谎）、访问控制（生物识别认证）、娱乐（电影、媒体和游戏）、视频会议（包括支持唇读）和医学（颅面整形手术计划和化妆品）方面有重要应用。

Face analysis and synthesis has become an inexhaustible research topic in both the scientific community and industry, driven by applications in human-computer interaction, security, and entertainment. State of the art 3D face models used for recognition or animation cannot represent and identify subtle differences in facial appearance or feature configuration necessary to uniquely discriminate among individuals. In this project, the PI will develop a novel technique for analysis and synthesis of the human face at a higher level of detail than it is currently possible to achieve. A so-called 3D topographic representation is proposed for labeling and modeling the facial surface, in which the face is represented by an active mesh with a variable resolution based on the surface curvatures and the topographic labels. The PI expects that tracing the behavior of some features across multiple scales will reveal precious information about the nature of the underlying physical process, and thus lead to establishing an intrinsic relationship between facial features and surface properties (i.e., peak, pit, ridge, ravine, saddle, hill, flat, etc). This will, in turn, provide a scientific understanding of how facial appearance and representation vary along with expression changes, in an intuitive and detailed manner, and will offer profound new insights into how 3D facial surfaces contain embedded features that are not exhibited in 2D planar images. The PI anticipates that this pilot research will eventually enable him to develop a "humanized" system for recognizing human faces and their expressions (even emotions), as well as an automatic system for generating life-like facial expressions.Broader Impacts: This research will improve our understanding of the cognitive processes involved in human vision, and impact the development of next generation human-computer interfaces in which machines can recognize facial expressions. The work will also have important applications in law enforcement (mug shot searches, security surveillance, and lie detection), access control (biometric authentication), entertainment (films, media, and games), videoconferencing (including support for lip-reading), and medicine (craniofacial plastic surgery planning, and cosmetics).