  Recently, many methods have been proposed for face reconstruction from
multiple images, most of which involve fundamental principles of Shape from
Shading and Structure from motion. However, a majority of the methods just
generate discrete surface model of face. In this paper, B-spline Shape from
Motion and Shading (BsSfMS) is proposed to reconstruct continuous B-spline
surface for multi-view face images, according to an assumption that shading and
motion information in the images contain 1st- and 0th-order derivative of
B-spline face respectively. Face surface is expressed as a B-spline surface
that can be reconstructed by optimizing B-spline control points. Therefore,
normals and 3D feature points computed from shading and motion of images
respectively are used as the 1st- and 0th- order derivative information, to be
jointly applied in optimizing the B-spline face. Additionally, an IMLS
(iterative multi-least-square) algorithm is proposed to handle the difficult
control point optimization. Furthermore, synthetic samples and LFW dataset are
introduced and conducted to verify the proposed approach, and the experimental
results demonstrate the effectiveness with different poses, illuminations,
expressions etc., even with wild images.
