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BMVC
2010
14 years 7 months ago
Improved Anatomical Landmark Localization in Medical Images Using Dense Matching of Graphical Models
We propose a method for reliably and accurately identifying anatomical landmarks in 3D CT volumes based on dense matching of parts-based graphical models. Such a system can be use...
Vaclav Potesil, Timor Kadir, Günther Platsch,...
CVPR
2007
IEEE
15 years 11 months ago
Hybrid learning of large jigsaws
A jigsaw is a recently proposed generative model that describes an image as a composition of non-overlapping patches of varying shape, extracted from a latent image. By learning t...
Julia A. Lasserre, Anitha Kannan, John M. Winn
CVPR
2000
IEEE
15 years 11 months ago
Towards Automatic Discovery of Object Categories
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
Markus Weber, Max Welling, Pietro Perona
ICCV
2005
IEEE
15 years 11 months ago
Efficient Learning of Relational Object Class Models
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall