Monocular simultaneous localization and map** (SLAM) algorithms perform robustly
when observing rigid scenes; however, they fail when the observed scene deforms, for …

A recent trend in Non-Rigid Structure-from-Motion (NRSfM) is to express local, differential
constraints between pairs of images, from which the surface normal at any point can be …

We study Isometric Non-Rigid Shape-from-Motion (Iso-NRSfM): given multiple intrinsically
calibrated monocular images, we want to reconstruct the time-varying 3D shape of a thin …

Non-rigid structure from motion (nrs fm), is a long standing and central problem in computer
vision and its solution is necessary for obtaining 3D information from multiple images when …

In this paper, we propose a sequential solution to simultaneously estimate camera pose and
non-rigid 3D shape from a monocular video. In contrast to most existing approaches that rely …

Shape-from-Template (SfT) reconstructs the shape of a deforming surface from a single
image, a 3D template and a deformation prior. For isometric deformations, this is a well …

Abstract Most Non-Rigid Structure from Motion (NRSfM) solutions are based on factorization
approaches that allow reconstructing objects parameterized by a sparse set of 3D points …

Deformable Monocular SLAM algorithms recover the localization of a camera in an unknown
deformable environment. Current approaches use a template-based deformable tracking to …

We present a global and convex formulation for the template-less 3D reconstruction of a
deforming object with the perspective camera. We show for the first time how to construct a …

Non-Rigid Structure-from-Motion (NRSfM) reconstructs a deformable 3D object from
keypoint correspondences established between monocular 2D images. Current NRSfM …