Université d'Auvergne Clermont1 | CNRS


Linear Formulations for Deformable Shape Reconstruction

20/09/2012 09:00
Francesc Moreno-Nogue

In this talk, I will first present an approach to the PnP problem -the
estimation of the pose of a calibrated camera from n point correspondences
between an image and a 3D model- whose computational complexity grows
linearly with n. Our central idea is to express the 3D points as a weighted
sum of four virtual control points. The problem then reduces to estimating
the coordinates of these control points in the camera referential, which can
be done in O(n) using simple linearization techniques. I will then show that
the same type of approach can be applied to register non-rigid 3D surfaces.
However, since monocular non-rigid reconstruction is severely
under-constrained we will have to consider additional constraints, either
based on local rigidity (to reconstruct deformable and inextensible
surfaces), or based on shading coherence (to reconstruct deformable and
stretchable surfaces).

In the final part of the talk, I will discuss the major limitations of these
linear formulations and propose a novel and alternative stochastic
exploration strategy. I will present results both for non-rigid shape and
human pose recovery.