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» On the Direct Estimation of the Fundamental Matrix
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IJCV
2000
133views more  IJCV 2000»
13 years 7 months ago
Heteroscedastic Regression in Computer Vision: Problems with Bilinear Constraint
We present an algorithm to estimate the parameters of a linear model in the presence of heteroscedastic noise, i.e., each data point having a different covariance matrix. The algor...
Yoram Leedan, Peter Meer
CVPR
2009
IEEE
15 years 2 months 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
ICCV
2001
IEEE
14 years 9 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...
TASLP
2010
141views more  TASLP 2010»
13 years 2 months ago
Adaptive Harmonic Spectral Decomposition for Multiple Pitch Estimation
Multiple pitch estimation consists of estimating the fundamental frequencies and saliences of pitched sounds over short time frames of an audio signal. This task forms the basis of...
Emmanuel Vincent, Nancy Bertin, Roland Badeau
CDC
2009
IEEE
130views Control Systems» more  CDC 2009»
13 years 11 months ago
Mixed linear system estimation and identification
We consider a mixed linear system model, with both continuous and discrete inputs and outputs, described by a coefficient matrix and a set of noise variances. When the discrete inp...
Argyrios Zymnis, Stephen P. Boyd, Dimitry M. Gorin...