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DAGM
2006
Springer
14 years 9 days ago
Linear vs. Nonlinear Feature Combination for Saliency Computation: A Comparison with Human Vision
In the heart of the computer model of visual attention, an interest or saliency map is derived from an input image in a process that encompasses several data combination steps. Whi...
Nabil Ouerhani, Alexandre Bur, Heinz Hügli
ECCV
2002
Springer
14 years 10 months ago
Robust Computer Vision through Kernel Density Estimation
Abstract. Two new techniques based on nonparametric estimation of probability densities are introduced which improve on the performance of equivalent robust methods currently emplo...
Haifeng Chen, Peter Meer
PAMI
2006
126views more  PAMI 2006»
13 years 8 months ago
Estimation of Nonlinear Errors-in-Variables Models for Computer Vision Applications
In an errors-in-variables (EIV) model, all the measurements are corrupted by noise. The class of EIV models with constraints separable into the product of two nonlinear functions, ...
Bogdan Matei, Peter Meer
DICTA
2003
13 years 10 months ago
FNS, CFNS and HEIV: Extending Three Vision Parameter Estimation Methods
Estimation of parameters from image tokens is a central problem in computer vision. FNS, CFNS and HEIV are three recently developed methods for solving special but important cases ...
Wojciech Chojnacki, Michael J. Brooks, Anton van d...
CVPR
1998
IEEE
14 years 10 months ago
Bagging in Computer Vision
Previous research has shown that aggregated predictors improve the performance of non-parametric function approximation techniques. This paper presents the results of applying agg...
Bruce A. Draper, Kyungim Baek