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» Shape Priors using Manifold Learning Techniques
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ICCV
2007
IEEE
13 years 11 months ago
Shape Priors using Manifold Learning Techniques
We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a category o...
Patrick Etyngier, Florent Ségonne, Renaud K...
MICCAI
2007
Springer
14 years 5 months ago
Active-Contour-Based Image Segmentation Using Machine Learning Techniques
Abstract. We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a c...
Patrick Etyngier, Florent Ségonne, Renaud K...
SCALESPACE
2007
Springer
13 years 11 months ago
Towards Segmentation Based on a Shape Prior Manifold
Incorporating shape priors in image segmentation has become a key problem in computer vision. Most existing work is limited to a linearized shape space with small deformation modes...
Patrick Etyngier, Renaud Keriven, Jean-Philippe Po...
CVPR
2011
IEEE
12 years 8 months ago
Nonlinear Shape Manifolds as Shape Priors in Level Set Segmentation and Tracking
We propose a novel nonlinear, probabilistic and variational method for adding shape information to level setbased segmentation and tracking. Unlike previous work, we represent sha...
Victor Prisacariu, Ian Reid
ICIP
2007
IEEE
14 years 6 months ago
Projection onto a Shape Manifold for Image Segmentation with Prior
Image segmentation with shape priors has received a lot of attention over the past years. Most existing work focuses on a linearized shape space with small deformation modes aroun...
Florent Ségonne, Patrick Etyngier, Renaud K...