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» On the Dimensionality of Face Space
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ECCV
2004
Springer
16 years 8 months ago
Face Recognition with Local Binary Patterns
In this work, we present a novel approach to face recognition which considers both shape and texture information to represent face images. The face area is first divided into small...
Abdenour Hadid, Matti Pietikäinen, Timo Ahone...
ICDM
2009
IEEE
125views Data Mining» more  ICDM 2009»
16 years 1 months ago
A Fully Automated Method for Discovering Community Structures in High Dimensional Data
—Identifying modules, or natural communities, in large complex networks is fundamental in many fields, including social sciences, biological sciences and engineering. Recently s...
Jianhua Ruan
AUSDM
2007
Springer
193views Data Mining» more  AUSDM 2007»
16 years 19 days ago
Are Zero-suppressed Binary Decision Diagrams Good for Mining Frequent Patterns in High Dimensional Datasets?
Mining frequent patterns such as frequent itemsets is a core operation in many important data mining tasks, such as in association rule mining. Mining frequent itemsets in high-di...
Elsa Loekito, James Bailey
CIKM
2008
Springer
15 years 8 months ago
On low dimensional random projections and similarity search
Random projection (RP) is a common technique for dimensionality reduction under L2 norm for which many significant space embedding results have been demonstrated. However, many si...
Yu-En Lu, Pietro Liò, Steven Hand
CVPR
2005
IEEE
16 years 8 months ago
Nonparametric Subspace Analysis for Face Recognition
Linear discriminant analysis (LDA) is a popular face recognition technique. However, an inherent problem with this technique stems from the parametric nature of the scatter matrix...
Zhifeng Li, Wei Liu, Dahua Lin, Xiaoou Tang