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MICCAI
2007
Springer
14 years 1 months ago
Robust Autonomous Model Learning from 2D and 3D Data Sets
In this paper we propose a weakly supervised learning algorithm for appearance models based on the minimum description length (MDL) principle. From a set of training images or volu...
Georg Langs, Rene Donner, Philipp Peloschek, Horst...
BMVC
2010
13 years 5 months ago
Back to the Future: Learning Shape Models from 3D CAD Data
Recognizing 3D objects from arbitrary view points is one of the most fundamental problems in computer vision. A major challenge lies in the transition between the 3D geometry of o...
Michael Stark, Michael Goesele, Bernt Schiele
NIPS
2003
13 years 8 months ago
Learning Non-Rigid 3D Shape from 2D Motion
This paper presents an algorithm for learning the time-varying shape of a non-rigid 3D object from uncalibrated 2D tracking data. We model shape motion as a rigid component (rotat...
Lorenzo Torresani, Aaron Hertzmann, Christoph Breg...
CVPR
2008
IEEE
14 years 1 months ago
3D face tracking and expression inference from a 2D sequence using manifold learning
We propose a person-dependent, manifold-based approach for modeling and tracking rigid and nonrigid 3D facial deformations from a monocular video sequence. The rigid and nonrigid ...
Wei-Kai Liao, Gérard G. Medioni
ECCV
2008
Springer
14 years 9 months ago
Robust 3D Pose Estimation and Efficient 2D Region-Based Segmentation from a 3D Shape Prior
In this work, we present an approach to jointly segment a rigid object in a 2D image and estimate its 3D pose, using the knowledge of a 3D model. We naturally couple the two proces...
Samuel Dambreville, Romeil Sandhu, Anthony J. Yezz...