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NECO
2011
14 years 11 months ago
Least Squares Estimation Without Priors or Supervision
Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...
Martin Raphan, Eero P. Simoncelli
CVPR
2009
IEEE
16 years 11 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
CVPR
2005
IEEE
16 years 6 months ago
Applying Neighborhood Consistency for Fast Clustering and Kernel Density Estimation
Nearest neighborhood consistency is an important concept in statistical pattern recognition, which underlies the well-known k-nearest neighbor method. In this paper, we combine th...
Kai Zhang, Ming Tang, James T. Kwok
ICCV
2007
IEEE
16 years 6 months ago
Shining a Light on Human Pose: On Shadows, Shading and the Estimation of Pose and Shape
Strong lighting is common in natural scenes yet is often viewed as a nuisance for object pose estimation and tracking. In human shape and pose estimation, cast shadows can be conf...
Alexandru O. Balan, Michael J. Black, Horst W. Hau...
ICCV
2001
IEEE
16 years 6 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...