3D shape measurement of human shape from multiple viewpoint images using shape database

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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.