Probabilistic Simultaneous Pose and Non-Rigid Shape Recovery

12 years 5 months ago
Probabilistic Simultaneous Pose and Non-Rigid Shape Recovery
We present an algorithm to simultaneously recover nonrigid shape and camera poses from point correspondences between a reference shape and a sequence of input images. The key novel contribution of our approach is in bringing the tools of the probabilistic SLAM methodology from a rigid to a deformable domain. Under the assumption that the shape may be represented as a weighted sum of deformation modes, we show that the problem of estimating the modal weights along with the camera poses, may be probabilistically formulated as a maximum a posterior estimate and solved using an iterative least squares optimization. An extensive evaluation on synthetic and real data, shows that our approach has several significant advantages over current approaches, such as performing robustly under large amounts of noise and outliers, and neither requiring to track points over the whole sequence nor initializations close from the ground truth solution.
Francesc Moreno (Institut de Robotica i Informatic
Added 30 Apr 2011
Updated 30 Apr 2011
Type Journal
Year 2011
Where CVPR
Authors Francesc Moreno (Institut de Robotica i Informatica Industrial, Josep Porta (Institut de Robotica i Informatica Industrial
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