1. A method for automatically reconstructing a 3D face from a plurality of 2D images of a human face, comprising: deriving initial camera position estimates using prior face knowledge of a generic face; selecting image pairs representing corresponding images from the plurality of 2D images that define similar poses and extracting sparse feature points representing perimeters of a face or locations of facial features for each of said image pairs; refining said initial camera position estimates and said sparse feature points; extracting dense 3D point clouds from said image pairs by performing dense feature detection and matching across said image pairs using a purely data-driven approach that does not use prior face knowledge or generic faces, wherein said dense feature matching identifies additional features beyond the sparse feature points; merging said dense 3D point clouds into a single 3D cloud; removing outliers from said single 3D cloud to form a cleaned 3D point cloud without using prior face knowledge or generic faces; fitting a connected surface to the cleaned 3D point cloud without using prior face knowledge or generic faces; and texture mapping surface detail and color information of a subject's face onto said connected surface.