Shape-from-X is a generic type of inverse problems in computer vision, in which a shape is reconstructed from some measurements. A specially challenging setting of this problem is the case in which the reconstructed shapes are non-rigid. In this paper, we propose a framework for intrinsic regularization of such problems. The assumption is that we have the geometric structure of a shape which is intrinsically (up to bending) similar to the one we would like 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.
Sung Shik KohThi Thi ZinHiromitsu Hama
Xavier LladóAlessio Del BueArnau OliverJoaquím SalvíLourdes Agapito
Guy RosmanMichael M. BronsteinAlexander M. BronsteinAlon WolfRon Kimmel
Kaiwen GuoFeng XuYangang WangYebin LiuQionghai Dai