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» A Statistical Shape Model without Using Landmarks
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ECCV
2000
Springer
14 years 10 months ago
Unsupervised Learning of Models for Recognition
We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...
Markus Weber, Max Welling, Pietro Perona
CIMAGING
2009
265views Hardware» more  CIMAGING 2009»
13 years 10 months ago
Multi-object segmentation using coupled nonparametric shape and relative pose priors
We present a new method for multi-object segmentation in a maximum a posteriori estimation framework. Our method is motivated by the observation that neighboring or coupling objec...
Mustafa Gökhan Uzunbas, Octavian Soldea, M&uu...
ISBI
2004
IEEE
14 years 9 months ago
Statistical Surface-Based Morphometry Using a Non-Parametric Approach
We present a novel method of statistical surface-based morphometry based on the use of non-parametric permutation tests. In order to evaluate morphologicaldifferences of brain str...
Dimitrios Pantazis, Richard M. Leahy, Thomas E. Ni...
MICCAI
2005
Springer
14 years 9 months ago
Deformable Registration of Brain Tumor Images Via a Statistical Model of Tumor-Induced Deformation
An approach to the deformable registration of three-dimensional brain tumor images to a normal brain atlas is presented. The approach involves the integration of three components:...
Ashraf Mohamed, Dinggang Shen, Christos Davatzikos
FGR
2004
IEEE
160views Biometrics» more  FGR 2004»
14 years 19 days ago
A Comparison of Shape Constrained Facial Feature Detectors
We consider the problem of robustly and accurately locating facial features. The relative positions of different feature points are represented using a statistical shape model. We...
David Cristinacce, Timothy F. Cootes