Poster: 3D-face model reconstruction utilizing facial shape database from multiple uncalibrated cameras

In recent years, a surveillance camera has come to be attached in various places from a rise of the consciousness to security. Since the surveillance cameras are installed in variety of place, it is possible to take a picture of the same person from multiple uncalibrated cameras though it is asynchronous. In this article, we propose a method for reconstructing a face shape from multiple-view images taken with non - synchronous multiple cameras. In this method, we do not directly reconstruct the shape, but estimate a small number of parameters which represent the face shape. The parameter space is constructed with Principal Component Analysis of database of a large number of anatomical face shapes collected for different people. From the input multiple view images, the region of the face and three feature points on the face are manually extracted. Then the facial pose is estimated by optimizing the evaluation based on the silhouette shape, appearance, and the position of the feature points. According to the facial pose, the parameters representing the facial shape are also estimated by optimizing the same evaluation function. Those optimizing procedures are repeated for obtaining the facial shape for the object face captured with the non-synchronous multiple cameras. The experimental results demonstrate the effectiveness of the proposed method. Since the database used in this paper consists of anatomically aligned shape data, we can obtain anatomical shape of the face, which is suitable to represent the identity of each person.