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» Strategies in Rigid-Variable Methods
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111
Voted
CVPR
2008
IEEE
16 years 2 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
CVPR
2008
IEEE
16 years 2 months ago
Physical simulation for probabilistic motion tracking
Human motion tracking is an important problem in computer vision. Most prior approaches have concentrated on efficient inference algorithms and prior motion models; however, few c...
Marek Vondrak, Leonid Sigal, Odest Chadwicke Jenki...
115
Voted
CVPR
2008
IEEE
16 years 2 months ago
Simultaneous super-resolution and 3D video using graph-cuts
This paper presents a new method to increase the quality of 3D video, a new media developed to represent 3D objects in motion. This representation is obtained from multi-view reco...
Tony Tung, Shohei Nobuhara, Takashi Matsuyama
110
Voted
ICCV
2003
IEEE
16 years 2 months ago
Real-Time Simultaneous Localisation and Mapping with a Single Camera
Ego-motion estimation for an agile single camera moving through general, unknown scenes becomes a much more challenging problem when real-time performance is required rather than ...
Andrew J. Davison
147
Voted
ECCV
2002
Springer
16 years 2 months ago
A Stochastic Algorithm for 3D Scene Segmentation and Reconstruction
In this paper, we present a stochastic algorithm by effective Markov chain Monte Carlo (MCMC) for segmenting and reconstructing 3D scenes. The objective is to segment a range image...
Feng Han, Zhuowen Tu, Song Chun Zhu