33 search results - page 2 / 7 » Robust Fundamental Matrix Estimation with Accurate Outlier D... |
CSDA
2007
13 years 7 months ago
2007
In this paper we address the problem of selecting variables or features in a regression model in the presence of both additive (vertical) and leverage outliers. Since variable sel...
ICPR
2002
IEEE
14 years 8 months ago
2002
IEEE
Robustness of parameter estimation relies on discriminating inliers from outliers within the set of correspondences. In this paper, we present a method using tensor voting to elim...
ECCV
2004
Springer
14 years 8 months ago
2004
Springer
Low-level image processing algorithms generally provide noisy features that are far from being Gaussian. Medium-level tasks such as object detection must therefore be robust to out...
CVPR
1998
IEEE
14 years 9 months ago
1998
IEEE
This paper addresses robust feature tracking. We extend the well-known Shi-Tomasi-Kanade tracker by introducing an automatic scheme for rejecting spurious features. We employ a si...
ECCV
2004
Springer
14 years 27 days ago
2004
Springer
Computer vision tasks often require the robust fit of a model to some data. In a robust fit, two major steps should be taken: i) robustly estimate the parameters of a model, and ii...