Variational methods have been employed with considerable success in computer vision,
particularly for surface reconstruction problems. Formulations of this type require the solution
of computationally complex Euler–Lagrange partial differential equations (PDEs) to obtain
the desired reconstructions. Further, the calculation of reconstruction error covariances for
such approaches are usually neglected. In this paper we describe a computationally efficient
multiscale approach to surface reconstruction which differs fundamentally from other …