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» Weighted and Robust Incremental Method for Subspace Learning
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CVPR
2010
IEEE
12 years 3 months ago
Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling
Robust tracking of abrupt motion is a challenging task in computer vision due to the large motion uncertainty. In this paper, we propose a stochastic approximation Monte Carlo (...
Xiuzhuang Zhou and Yao Lu
ICCV
2003
IEEE
14 years 7 months ago
Ranking Prior Likelihood Distributions for Bayesian Shape Localization Framework
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood ...
Shuicheng Yan, Mingjing Li, HongJiang Zhang, QianS...
ICPR
2006
IEEE
14 years 7 months ago
Recognizing Facial Expressions by Tracking Feature Shapes
Reliable facial expression recognition by machine is still a challenging task. We propose a framework to recognise various expressions by tracking facial features. Our method uses...
Atul Kanaujia, Dimitris N. Metaxas
CVPR
2008
IEEE
14 years 8 months ago
A deformable local image descriptor
This paper presents a novel local image descriptor that is robust to general image deformations. A limitation with traditional image descriptors is that they use a single support ...
Hong Cheng, Zicheng Liu, Nanning Zheng, Jie Yang
ISVC
2009
Springer
14 years 15 days ago
Combinatorial Preconditioners and Multilevel Solvers for Problems in Computer Vision and Image Processing
Abstract. Linear systems and eigen-calculations on symmetric diagonally dominant matrices (SDDs) occur ubiquitously in computer vision, computer graphics, and machine learning. In ...
Ioannis Koutis, Gary L. Miller, David Tolliver