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» Application of Level Set Methods in Computer Vision
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CVPR
2006
IEEE
14 years 1 months ago
New Method of Probability Density Estimation with Application to Mutual Information Based Image Registration
We present a new, robust and computationally efficient method for estimating the probability density of the intensity values in an image. Our approach makes use of a continuous r...
Ajit Rajwade, Arunava Banerjee, Anand Rangarajan
ICCV
1999
IEEE
13 years 11 months ago
Learning Low-Level Vision
We describe a learning-based method for low-level vision problems--estimating scenes from images. We generate a synthetic world of scenes and their corresponding rendered images, m...
William T. Freeman, Egon C. Pasztor
ECCV
2010
Springer
14 years 26 days ago
Converting Level Set Gradients to Shape Gradients
The level set representation of shapes is useful for shape evolution and is widely used for the minimization of energies with respect to shapes. Many algorithms consider energies d...
ICPR
2006
IEEE
14 years 8 months ago
Reconciling Landmarks and Level Sets
Shape warping is a key problem in statistical shape analysis. This paper proposes a framework for geometric shape warping based on both shape distances and landmarks. Our method i...
Olivier D. Faugeras, Pierre Maurel, Renaud Keriven
CVPR
2011
IEEE
12 years 11 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