| Project/Area Number |
07680399
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Nara Institute of Science and Technology |
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Principal Investigator |
YOKOYA Naokazu Graduate School of Information Science, Nara Institute of Science and Technology, Professor, 情報科学研究科, 教授 (10252834)
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| Co-Investigator(Kenkyū-buntansha) |
KATAYAMA Yoshiaki Information Technology Center, Nara Institute of Science and Technology, Reseach, 情報科学センター, 助手 (10263435)
IWASA Hidehiko Graduate School of Information Science, Nara Institute of Science and Technology, 情報科学研究科, 助手 (50263447)
TAKEMURA Haruo Graduate School of Information Science, Nara Institute of Science and Technology, 情報科学研究科, 助教授 (60263430)
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| Project Period (FY) |
1995 – 1996
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| Project Status |
Completed (Fiscal Year 1996)
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| Budget Amount *help |
¥2,000,000 (Direct Cost: ¥2,000,000)
Fiscal Year 1996: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 1995: ¥1,400,000 (Direct Cost: ¥1,400,000)
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| Keywords | Facial Image Processing / Expression Analysis / Expression Synthesis / 3D Measurement / Cylindrical range Image / 3D Shape Analysis / Image Warping / Facial Animation |
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| Research Abstract |
We have obtained the following research results in this project.
1. Three-dimendional Measurement of Faces Firstly faces of more than thirty testees were measured in neutral and six primary expressions (anger, disgust, surprise, fear, happiness, sadness) by using a laser rangefinder. Both cylindrical range and surface color images were obtained in this measurement. In order to remove the influence of pose and position of testees, we defined an object-centered coordinate system on a face. Preliminary experiments have shown that the employed feature point representation is approximately invariant to variations of facial shapes.
2. Three-dimensional Shape Analysis of Faces Using Range Images We have developed a method of quantifying six primary facial expressions by computing 3D motion vectors at feature points in range images during expressions. Such motion vectors indicate the facial deformation during expressions. We have also developed a method of automatically extracting facial compone
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nts from color images as well as that of face recognition based on a subspace method using range images. It has been observed that the mosaicing of images increases the recognition rate.
3. Image Warping for Range Images A framework of generating a 3D facial expression image from a neutral image has been established . The method is based upon applying an image warping technique to range and surface color images. The image warping employed is based upon radial basis functions. Now we can generate facial images with six primary expressions from an image with neutral expression. The subjective evaluation has been conducted for evaluating the quality of generated images.
4. Facial Animation with Expressions The facial animation is computed by gradually changing the magnitude of expression in the process of generating facial images with six primary expressions, which is mentioned above. Moreover, we have investigated in the motion animation based on dynamics using a musculoskeletal model toward the future research. Less
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