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» Robust Autonomous Model Learning from 2D and 3D Data Sets
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MICCAI
2009
Springer
16 years 5 months ago
Building Shape Models from Lousy Data
Statistical shape models have gained widespread use in medical image analysis. In order for such models to be statistically meaningful, a large number of data sets have to be inclu...
Marcel Lüthi, Thomas Albrecht, Thomas Vetter
203
Voted
PAMI
2010
417views more  PAMI 2010»
15 years 2 months ago
Auto-Context and Its Application to High-Level Vision Tasks and 3D Brain Image Segmentation
The notion of using context information for solving high-level vision and medical image segmentation problems has been increasingly realized in the field. However, how to learn a...
Zhuowen Tu, Xiang Bai
117
Voted
ICCS
2005
Springer
15 years 9 months ago
Dynamic Data Driven Coupling of Continuous and Discrete Methods for 3D Tracking
We present a new framework for robust 3D tracking, using a dynamic data driven coupling of continuous and discrete methods to overcome their limitations. Our method uses primarily ...
Dimitris N. Metaxas, Gabriel Tsechpenakis
ICCV
2011
IEEE
14 years 4 months ago
Automated Articulated Structure and 3D Shape Recovery from Point Correspondences
In this paper we propose a new method for the simultaneous segmentation and 3D reconstruction of interest point based articulated motion. We decompose a set of point tracks into r...
Joao Fayad, Chris Russell, Lourdes Agapito
146
Voted
HLK
2003
IEEE
15 years 9 months ago
Regularized 3D Morphable Models
Three-dimensional morphable models of object classes are a powerful tool in modeling, animation and recognition. We introduce here the new concept of regularized 3D morphable mode...
Curzio Basso, Thomas Vetter, Volker Blanz