| Project/Area Number |
22300070
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Perception information processing/Intelligent robotics
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| Research Institution | Waseda University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
SHIMADA Kazuyuki 鹿児島大学, 医歯(薬)学総合研究科, 教授 (80130524)
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| Project Period (FY) |
2010 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥18,460,000 (Direct Cost: ¥14,200,000、Indirect Cost: ¥4,260,000)
Fiscal Year 2012: ¥5,070,000 (Direct Cost: ¥3,900,000、Indirect Cost: ¥1,170,000)
Fiscal Year 2011: ¥5,720,000 (Direct Cost: ¥4,400,000、Indirect Cost: ¥1,320,000)
Fiscal Year 2010: ¥7,670,000 (Direct Cost: ¥5,900,000、Indirect Cost: ¥1,770,000)
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| Keywords | ディジタルヒューマンモデル / 顔の分析・合成 / 解剖学的顔モデル / 年齢・性別変換 / 顔認証 / ３次元顔形状推定 / コンピュータビジョン / 画像情報処理 / 顔形状3次元復元 / 年齢変化シミュレーション / 表情合成モデル / デジタルヒューマンモデル |
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| Research Abstract |
In the several properties of human face, we focused on personal characteristics, age, emotion and health condition, and then a parametric face model has been realized with high reality and accuracy. First of all, we produced an individual face model with variation of muscles location and fat layer structure on face by anatomical analysis of real face by collaboration with Prof. Shimada. Next, we found the statistical rules in a human face structure and constructed a generic 3D face model by analysis of huge face database including 3D range scan data and frontal snap shots. At first, we proposed the algorithm to extract feature points stably and robustly on frontal face image by linear predictors. Then we proposed new method to extract individual 3D feature of face accurately and constructed a real-time and automatic 3D face reconstruction system by camera captured photo. Also we found the wrinkles are very important to produce an aged face, and then we constructed an interactive aged face simulator by controlling shape of face, textures and wrinkles. Moreover, based on this proposed face model generation platform, we contributed to the research area of face image processing strongly by proposing a face authentication system robust to aging effect, driver’s drowsiness estimation system, face image synthesis system with wrinkles control, lip synchronization system and face recognition system between natural and artificial smile.
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