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

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:
$10.0万
依托单位:
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
项目状态:
已结题
起止时间:
2004-04-01 至 2006-03-31

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中文摘要
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英文摘要
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).
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CI-SUSTAIN: Collaborative Research: Extending a Large Multimodal Corpus of Spontaneous Behavior for Automated Emotion Analysis
  • 批准号:
    1629898
  • 项目类别:
    Standard Grant
  • 资助金额:
    $48.36万
  • 财政年份:
    2016
  • 负责人:
    Lijun Yin
  • 依托单位:
CI-ADDO-EN: Collaborative Research: 3D Dynamic Multimodal Spontaneous Emotion Corpus for Automated Facial Behavior and Emotion Analysis
  • 批准号:
    1205664
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.68万
  • 财政年份:
    2012
  • 负责人:
    Lijun Yin
  • 依托单位:
EAGER: Spontaneous 4D-Facial Expression Corpus for Automated Facial Image Analysis
  • 批准号:
    1051103
  • 项目类别:
    Standard Grant
  • 资助金额:
    $6.58万
  • 财政年份:
    2010
  • 负责人:
    Lijun Yin
  • 依托单位:
SGER: Analyzing Facial Expression in Three Dimensional Space
  • 批准号:
    0541044
  • 项目类别:
    Standard Grant
  • 资助金额:
    $0.0万
  • 财政年份:
    2005
  • 负责人:
    Lijun Yin
  • 依托单位:
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