| Budget Amount *help |
¥2,300,000 (Direct Cost: ¥2,300,000)
Fiscal Year 1997: ¥100,000 (Direct Cost: ¥100,000)
Fiscal Year 1996: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 1995: ¥1,500,000 (Direct Cost: ¥1,500,000)
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| Research Abstract |
Novel approaches to generate 3D facial model and obtain facial expression data were proposed with an aim of presenting real CG facial animations.
For generating 3D facial model, a real time 3D measurement system was employed. The system, however, cannot measure a surface with large inclination against the system or a surface which does not reflect the light.
So, a method to generate 3D facial model which has no defects was proposed as a fundamental research of generating facial expression. The method measures an expressionless face with shaking one's head, then defects data are interpolated with another data one after another and measurement errors are also revised. At first, an initial 3D facial model is generated using measured data at the beggining. And then, the 3D facial model is interpolated and revised in order to compare with the data measured one after another.
On the other hand, Generating a 3D facial expression data is employed motion capturing system as an input device and sim
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plified muscle model as facial expression model.
As the research of psychology, the emotional human expressions consists of six kinds of expression such as anger, sadness, fear, disgust, surprise and happiness. And the expressions are common to all nations. In this research, these six kinds facial expression data are measured and represented.
The motion capturing system can measure motions of any points. It is a question how to operate 3D facial model based on the measured data. So, the proposed method employs the knowledge of anatomy such that the human facial expression is made by contraction of mimic muscles. Say in other words, in order to obtain movements of 17 mimic muscles using the motion capturing system, 13 feature points on the face are measured. The movement of the feature points are transformed to contraction ratio of mimic muscles, then the data are applied to the 3D facial model. In the 3D facial model, a simplifed muscle model is defined on the 3D facial wireflame model, and facial expressions are presented by operating the wireflame model. Less
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