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» Parameter Estimation Using Kalman Filters with Constraints
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CVPR
2003
IEEE
14 years 9 months ago
Optimal Segmentation of Dynamic Scenes from Two Perspective Views
We present a novel algorithm for optimally segmenting dynamic scenes containing multiple rigidly moving objects. We cast the motion segmentation problem as a constrained nonlinear...
René Vidal, Shankar Sastry
ICIP
2005
IEEE
14 years 9 months ago
An adaptive segmentation-based regularization term for image restoration
This paper proposes an original inhomogeneous restoration (deconvolution) model under the Bayesian framework. In this model, regularization is achieved, during the iterative resto...
Max Mignotte
IPMI
2007
Springer
14 years 8 months ago
Adaptive Time-Frequency Models for Single-Trial M/EEG Analysis
Abstract. A new method is introduced for estimating single-trial magnetoor electro-encephalography (M/EEG), based on a non-linear fit of timefrequency atoms. The method can be appl...
Christian Bénar, Maureen Clerc, Théo...
DAGM
1999
Springer
13 years 11 months ago
A Total Least Squares Framework for Low-Level Analysis of Dynamic Scenes and Processes
Abstract. We present a new method to simultaneously estimate optical flow fields and parameters of dynamic processes, violating the standard brightness change constraint equation...
Horst W. Haussecker, Christoph S. Garbe, Hagen Spi...
NIPS
1996
13 years 8 months ago
Radial Basis Function Networks and Complexity Regularization in Function Learning
In this paper we apply the method of complexity regularization to derive estimation bounds for nonlinear function estimation using a single hidden layer radial basis function netwo...
Adam Krzyzak, Tamás Linder