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CVPR
2007
IEEE
14 years 7 months ago
Simultaneous Covariance Driven Correspondence (CDC) and Transformation Estimation in the Expectation Maximization Framework
This paper proposes a new registration algorithm, Covariance Driven Correspondences (CDC), that depends fundamentally on the estimation of uncertainty in point correspondences. Th...
Michal Sofka, Gehua Yang, Charles V. Stewart
ICCV
2001
IEEE
14 years 7 months ago
What Value Covariance Information in Estimating Vision Parameters?
Many parameter estimation methods used in computer vision are able to utilise covariance information describing the uncertainty of data measurements. This paper considers the valu...
Michael J. Brooks, Wojciech Chojnacki, Darren Gawl...
ICPR
2008
IEEE
13 years 11 months ago
Improving Bayesian Network parameter learning using constraints
This paper describes a new approach to unify constraints on parameters with training data to perform parameter estimation in Bayesian networks of known structure. The method is ge...
Cassio Polpo de Campos, Qiang Ji
CVPR
2009
IEEE
15 years 12 days ago
StaRSaC: Stable Random Sample Consensus for Parameter Estimation
We address the problem of parameter estimation in presence of both uncertainty and outlier noise. This is a common occurrence in computer vision: feature localization is perform...
Jongmoo Choi, Gérard G. Medioni
EUROPAR
2001
Springer
13 years 9 months ago
Parallel Implementation of a Block Algorithm for Matrix 1-Norm Estimation
Abstract. We describe a parallel Fortran 77 implementation, in ScaLAPACK style, of a block matrix 1-norm estimator of Higham and Tisseur. This estimator differs from that underlyi...
Sheung Hun Cheng, Nicholas J. Higham