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ICCV
2005
IEEE
13 years 10 months ago
Learning the Probability of Correspondences without Ground Truth
We present a quality assessment procedure for correspondence estimation based on geometric coherence rather than ground truth. The procedure can be used for performance evaluation...
Qingxiong Yang, R. Matt Steele, David Nisté...
PAMI
2011
12 years 11 months ago
Learning Linear Discriminant Projections for Dimensionality Reduction of Image Descriptors
This paper proposes a general method for improving image descriptors using discriminant projections. Two methods based on Linear Discriminant Analysis have been recently introduce...
Hongping Cai, Krystian Mikolajczyk, Jiri Matas
ICTAI
2008
IEEE
13 years 11 months ago
Veritas: Combining Expert Opinions without Labeled Data
We consider a variation of the problem of combining expert opinions for the situation in which there is no ground truth to use for training. Even though we don’t have labeled da...
Sharath R. Cholleti, Sally A. Goldman, Avrim Blum,...
AROBOTS
2011
12 years 11 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox
ICCV
2005
IEEE
14 years 6 months ago
Vehicle Identification between Non-Overlapping Cameras without Direct Feature Matching
We propose a novel method for identifying road vehicles between two non-overlapping cameras. The problem is formulated as a same-different classification problem: probability of t...
Ying Shan, Harpreet S. Sawhney, Rakesh Kumar