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» Objective reduction using a feature selection technique
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DAGM
2005
Springer
14 years 2 months ago
Improving a Discriminative Approach to Object Recognition Using Image Patches
In this paper we extend a method that uses image patch histograms and discriminative training to recognize objects in cluttered scenes. The method generalizes and performs well for...
Thomas Deselaers, Daniel Keysers, Hermann Ney
IVC
2007
95views more  IVC 2007»
13 years 9 months ago
Models from image triplets using epipolar gradient features
In an application where sparse matching of feature points is used towards fast scene reconstruction, the choice of the type of features to be matched has an important impact on th...
Étienne Vincent, Robert Laganière
ISCC
2005
IEEE
14 years 2 months ago
A Label Space Reduction Algorithm for P2MP LSPs Using Asymmetric Tunnels
- Traffic Engineering objective is to optimize network resource utilization. Although several works have been published about minimizing network resource utilization, few works hav...
Fernando Solano, Ramón Fabregat, Yezid Dono...
CVPR
2006
IEEE
14 years 11 months ago
Multiclass Object Recognition with Sparse, Localized Features
We apply a biologically inspired model of visual object recognition to the multiclass object categorization problem. Our model modifies that of Serre, Wolf, and Poggio. As in that...
Jim Mutch, David G. Lowe
RT
2005
Springer
14 years 2 months ago
Importance Resampling for Global Illumination
This paper develops importance resampling into a variance reduction technique for Monte Carlo integration. Importance resampling is a sample generation technique that can be used ...
Justin Talbot, David Cline, Parris K. Egbert