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» Bayesian 3D Modeling from Images Using Multiple Depth Maps
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ICIAP
2001
Springer
15 years 10 months ago
Bayesian Face Recognition with Deformable Image Models
We propose a novel representation for characterizing image differences using a deformable technique for obtaining pixel-wise correspondences. This representation, which is based o...
Baback Moghaddam, Chahab Nastar, Alex Pentland
TIP
2008
139views more  TIP 2008»
14 years 9 months ago
Model-Based 2.5-D Deconvolution for Extended Depth of Field in Brightfield Microscopy
Abstract--Due to the limited depth of field of brightfield microscopes, it is usually impossible to image thick specimens entirely in focus. By optically sectioning the specimen, t...
François Aguet, Dimitri Van De Ville, Micha...
3DIM
1997
IEEE
15 years 2 months ago
Robust Meshes from Multiple Range Maps
This paper presents a method for modeling the surface of an object from a sequence of range maps. Our method is based on a volumetric approach that produces a compact surface with...
Kari Pulli, Tom Duchamp, Hugues Hoppe, John Alan M...
MICCAI
2002
Springer
15 years 10 months ago
A Statistical Shape Model for the Liver
The use of statistical shape models is a promising approach for robust segmentation of medical images. One of the major challenges in building a 3D shape model from a training set ...
Hans Lamecker, Thomas Lange, Martin Seebass
DAGM
2009
Springer
15 years 4 months ago
A Superresolution Framework for High-Accuracy Multiview Reconstruction
We present a variational approach to jointly estimate a displacement map and a superresolution texture for a 3D model from multiple calibrated views. The superresolution image form...
Bastian Goldlücke, Daniel Cremers