A reconstruction of a human face shape from a single image is an important theme for criminal investigation such as recognition of suspected people from surveillance cameras with only a few frames. It is, however, still difficult to recover a face shape from a non-frontal face image. Method using shading cues on a face depends on the lighting circumstance and cannot be adapted to images in which shadows occurs, for example [Kemelmacher et al. 2011]. On the other hand, [Blanz et al. 2004] reconstructed a shape by 3D Morphable Model (3DMM) only with facial feature points. This method, however, requires the pose-wise correspondences of vertices in the model to feature points of input image because a face contour cannot be seen when the facial direction is not the front. In this paper, we propose a method which can reconstruct a facial shape from a non-frontal face image only with a single general correspondence table. Our method searches for the correspondences of points on a facial contour in the iterative reconstruction process, and makes the reconstruction simple and stable.