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

SGER：开发高清人脸建模系统，用于人脸和面部表情的识别和生成

• 批准号: 0414029
• 负责人: Lijun Yin
• 金额: $ 10万
• 依托单位: SUNY at Binghamton
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-04-01 至 2006-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0414029&HistoricalAwards=false
• 关键词: SGER; Developing; definition; face; modeling

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).

人脸分析和合成已经成为科学界和工业界取之不尽的研究课题，受到人机交互，安全和娱乐应用的推动。 用于识别或动画的现有技术的3D面部模型不能表示和识别面部外观或特征配置中的细微差异，这些细微差异是唯一区分个体所必需的。 在这个项目中，PI将开发一种新的技术，用于分析和合成比目前可能实现的更高层次的人脸细节。 一个所谓的三维地形表示提出了标记和建模的面部表面，其中的脸是由一个活动的网格与可变分辨率的基础上的表面曲率和地形标签。 PI预计，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性质的宝贵信息，从而导致建立面部特征和表面属性之间的内在关系（即，峰、坑、脊、沟、鞍、山、平等）。 这将反过来，提供一个科学的理解，面部外观和表示如何随着表情的变化沿着变化，在一个直观和详细的方式，并将提供深刻的新的见解，如何三维面部表面包含嵌入式功能，不显示在二维平面图像。 PI预计，这项试点研究最终将使他能够开发出一种“人性化”的系统，用于识别人脸及其表情（甚至是情绪），以及一个自动系统，用于生成逼真的面部表情。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，其中机器可以识别面部表情。 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（包括唇读支持）和医学（颅面整形手术规划和化妆品）方面有重要的应用。