Double Spline Muscle Models for Human Face Animation based on Video Analysis

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Author(s)
Tang, SS
Liew, AWC
Yan, H
Griffith University Author(s)
Year published
2004
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Facial animation has been widely used in different areas such as entertainment and teleconferencing. Using video data to control facial animation is an interesting and difficult problem. In this paper, a novel double B-spline (NURBS) muscle system is proposed to simulate a 3D facial expression and talking animation based on video images. This system can simulate many different expressions of the elastic human face. Each muscle is constructed by two non-uniform rational B-spline curves, which better approximate the real muscle system. There are 14 feature points to represent facial expressions and we apply a lip contour ...
View more >Facial animation has been widely used in different areas such as entertainment and teleconferencing. Using video data to control facial animation is an interesting and difficult problem. In this paper, a novel double B-spline (NURBS) muscle system is proposed to simulate a 3D facial expression and talking animation based on video images. This system can simulate many different expressions of the elastic human face. Each muscle is constructed by two non-uniform rational B-spline curves, which better approximate the real muscle system. There are 14 feature points to represent facial expressions and we apply a lip contour extraction technique to determine lip shapes.
View less >
View more >Facial animation has been widely used in different areas such as entertainment and teleconferencing. Using video data to control facial animation is an interesting and difficult problem. In this paper, a novel double B-spline (NURBS) muscle system is proposed to simulate a 3D facial expression and talking animation based on video images. This system can simulate many different expressions of the elastic human face. Each muscle is constructed by two non-uniform rational B-spline curves, which better approximate the real muscle system. There are 14 feature points to represent facial expressions and we apply a lip contour extraction technique to determine lip shapes.
View less >
Conference Title
PROCEEDINGS OF THE 2004 INTERNATIONAL SYMPOSIUM ON INTELLIGENT MULTIMEDIA, VIDEO AND SPEECH PROCESSING
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