|Title:||Shape reconstruction with intrinsic priors
|Authors:||Yohai S. Devir, Guy Rosman, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
|Abstract:||Shape-from-X, a problem of shape reconstruction from some measurements, is a classical inverse problem in computer vision. In this paper, we propose a framework for intrinsic regularization of such problems. The assumption is that we have a shape intrinsically similar to (a bending of) the unknown shape we have to reconstruct. For that goal, we formulate a variation with respect to vertex coordinates of a triangulated-mesh approximating the continuous shape. The numerical core of the proposed method is based on differentiating the fast marching update step for geodesic distance computation.|
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