| Project/Area Number |
17500119
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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 |
Perception information processing/Intelligent robotics
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| Research Institution | Keio University |
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Principal Investigator |
SAITO HIDEO Keio University, Department of Information and Computer Science, Professor (90245605)
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| Co-Investigator(Kenkyū-buntansha) |
MOCHIMARU MASAAKI Digital Human Research Center, Advanced Institute of Science and Technology, Vice-Leader of the Center (90358169)
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| Project Period (FY) |
2005 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥3,630,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥330,000)
Fiscal Year 2007: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2006: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2005: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Keywords | Multiple Viewpoint Cameras / Unsynchronized Cameras / Human Shape Measurement / Facial Shape Measurement / Projector / Principal Component Analysis / Anatomical Human Shane Database / Hand-held Cameras / 移動カメラ画像列 / 多視点画像 / 形状データベース |
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| Research Abstract |
The purpose of this research project is establish a method for measuring 3D shapes of human parts with approximate 1mm accuracy from multiple viewpoint images by using database that consists of several hundreds 3D shapes of human parts.
In this research, we first pursue a method for measuring food shape from fixed and calibrated multiple cameras, and then have developed a pilot system that can easily reconstruct the shapes of foot shapes. By extending this method, we also established a method for recovering the shape of human facial/head area from an image sequence that captures multiple viewpoint images of the facial/head area with a handy camera that is moved freely by hand. In addition to this achievement, we also proposed a method for reconstructing facial shape from a frontal view image. Finally we extend those methods to a method for recovering facial shape from multiple viewpoint images taken by uncalibrated and unsynchronized multiple cameras, where we assume a situation that a object human's face is captured by surveillance cameras that are widely used for security purpose.
As results, we demonstrated the effectiveness of the proposed methods : 1) the method for reconstructing food shape from multiple calibrated cameras, 2) the method for reconstructing facial/head area shape from multiple viewpoint images that are captured with a handy camera moving freely with a hand, 3) the method for reconstructing facial/head area shape from a single image captured from the front of the face with a single point illumination placed at the same position of the camera, and 4) the method for reconstructing facial/head area shape from a single image captured from the front of the face with a single point illumination placed at the same position of the camera, and 5) the method for reconstructing facial/head area shape from multiple viewpoint images captured with uncalibrated and unsynchronized multiple cameras.
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