Thin plate spline (TPS) transformations have been applied to non-rigid shape matching with impressive results. However, existing methods often use a sparse set of point correspondences which are established prior to shape matching. A straightforward approach to finding point correspondences and computing TPS parameters imposes expensive computations, thereby motivating us to develop an efficient solution. In this paper, we present a direct method for recovering non-rigid object motion from its appearance in which the point correspondences are simultaneously established while estimating TPS parameters. The motion parameters are estimated in a stiff-to-flexible approach and the principal appearance deformations are learned that can be utilized for motion analysis and recognition. Numerous experiments demonstrate the efficiency and efficacy of the proposed algorithm in modeling the motion details of non-rigid objects undergoing shape deformation and pose variation.
['Jongwoo Lim', 'Ming-Hsuan Yang']
A direct method for modeling non-rigid motion with thin plate spline