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IVC
2006
129views more  IVC 2006»
13 years 8 months ago
Measuring the performance of face localization systems
The purpose of Face localization is to determine the coordinates of a face in a given image. It is a fundamental research area in computer vision because it serves, as a necessary...
Yann Rodriguez, Fabien Cardinaux, Samy Bengio, Joh...
KAIS
2006
87views more  KAIS 2006»
13 years 8 months ago
Improving the performance of 1D object classification by using the Electoral College
Abstract It has been proven that districted matching schemes (e.g., the US presidential election scheme, also called the Electoral College) are more stable than undistricted matchi...
Liang Chen, Ruoyu Chen, Sharmin Nilufar
PAMI
2008
391views more  PAMI 2008»
13 years 8 months ago
Riemannian Manifold Learning
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Tong Lin, Hongbin Zha
PAMI
2008
152views more  PAMI 2008»
13 years 8 months ago
Class-Based Feature Matching Across Unrestricted Transformations
We develop a novel method for class-based feature matching across large changes in viewing conditions. The method (called MBE) is based on the property that when objects share a si...
Evgeniy Bart, Shimon Ullman
PR
2008
123views more  PR 2008»
13 years 8 months ago
Extensions of vector quantization for incremental clustering
In this paper, we extend the conventional vector quantization by incorporating a vigilance parameter, which steers the tradeoff between plasticity and stability during incremental...
Edwin Lughofer