Augmenting images of non-rigid scenes using point and curve correspondences

Our goal is to augment images of non-rigid scenes coming from single-camera footage. We do not assume any a priori information about the scene being viewed, such as for example a parameterized 3D model or the motion of the camera. One possible solution is to use non-rigid factorization of points, from which a dense interpolating function modeled by a thin-plane spline can be computed. However, in many cases, point correspondences fail to capture precisely all the deformations occurring in the scene. Examples include the eyebrows or the lips when augmenting sequences of a face. Such deformations can be captured by tracking curves, but then point correspondences are not obtained directly due to the aperture problem. We propose an integrated method for non-rigid factorization and thin-plate spline interpolant estimation using point and curve correspondences over multiple views. The main novelties lie in the introduction of curves into the non-rigid factorization framework and in a direct global solution for the registration map, obtained by minimizing the registration error over all points and curves while taking all the images into account. The parameters of the registration map are set using cross-validation. The fidelity of the map is demonstrated by augmenting video footage undergoing various types of deformation.