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» A Statistical Shape Model without Using Landmarks
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ECCV
2000
Springer
15 years 11 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»
14 years 11 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
15 years 10 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
15 years 10 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»
15 years 1 months 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