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» Combining Simple Discriminators for Object Discrimination
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CVPR
2005
IEEE
14 years 11 months ago
Selection and Fusion of Color Models for Feature Detection
The choice of a color space is of great importance for many computer vision algorithms (e.g. edge detection and object recognition). It induces the equivalence classes to the actu...
Harro M. G. Stokman, Theo Gevers
PAMI
2007
156views more  PAMI 2007»
13 years 8 months ago
Selection and Fusion of Color Models for Image Feature Detection
—The choice of a color model is of great importance for many computer vision algorithms (e.g., feature detection, object recognition, and tracking) as the chosen color model indu...
Harro M. G. Stokman, Theo Gevers
ECCV
2008
Springer
14 years 10 months ago
Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features
Abstract. Recently, impressive results have been reported for the detection of objects in challenging real-world scenes. Interestingly however, the underlying models vary greatly e...
Paul Schnitzspan, Mario Fritz, Bernt Schiele
ECML
2006
Springer
14 years 15 days ago
Fisher Kernels for Relational Data
Abstract. Combining statistical and relational learning receives currently a lot of attention. The majority of statistical relational learning approaches focus on density estimatio...
Uwe Dick, Kristian Kersting
ICPR
2008
IEEE
14 years 4 months ago
Online Feature Evaluation For Object Tracking Using Kalman Filter
An online feature evaluation method for visual object tracking is put forward in this paper. Firstly, a combined feature set is built using color histogram (HC) bins and gradien...
Zhenjun Han, Qixiang Ye, Jianbin Jiao+