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» Parameter Estimation Using Kalman Filters with Constraints
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ICMLA
2007
13 years 8 months ago
Uncertainty optimization for robust dynamic optical flow estimation
We develop an optical flow estimation framework that focuses on motion estimation over time formulated in a Dynamic Bayesian Network. It realizes a spatiotemporal integration of ...
Volker Willert, Marc Toussaint, Julian Eggert, Edg...
DAGM
2010
Springer
13 years 8 months ago
Geometrically Constrained Level Set Tracking for Automotive Applications
We propose a new approach for integrating geometric scene knowledge into a level-set tracking framework. Our approach is based on a novel constrained-homography transformation mode...
Esther Horbert, Dennis Mitzel, Bastian Leibe
MICCAI
2002
Springer
14 years 8 months ago
Stochastic Finite Element Framework for Cardiac Kinematics Function and Material Property Analysis
Abstract. A stochastic finite element method (SFEM) based framework is proposed for the simultaneous estimation of cardiac kinematics functions and material model parameters. While...
Pengcheng Shi, Huafeng Liu
NIPS
2004
13 years 8 months ago
Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation
Bayesian Regularization and Nonnegative Deconvolution (BRAND) is proposed for estimating time delays of acoustic signals in reverberant environments. Sparsity of the nonnegative f...
Yuanqing Lin, Daniel D. Lee
JMLR
2006
169views more  JMLR 2006»
13 years 7 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...