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» Robust Autonomous Model Learning from 2D and 3D Data Sets
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MICCAI
2009
Springer
15 years 10 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
PAMI
2010
417views more  PAMI 2010»
14 years 8 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
ICCS
2005
Springer
15 years 3 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
13 years 9 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
80
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HLK
2003
IEEE
15 years 2 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