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» Robust Principal Component Analysis for Computer Vision
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ICIP
2005
IEEE
14 years 1 months ago
View independent face recognition based on kernel principal component analysis of local parts
This paper presents a view independent face recognition method based on kernel principal component analysis (KPCA) of local parts. View changes induce large variation in feature s...
Koji Hotta
CORR
2007
Springer
167views Education» more  CORR 2007»
13 years 7 months ago
Optimal Solutions for Sparse Principal Component Analysis
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonze...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
BMCBI
2005
201views more  BMCBI 2005»
13 years 7 months ago
Principal component analysis for predicting transcription-factor binding motifs from array-derived data
Background: The responses to interleukin 1 (IL-1) in human chondrocytes constitute a complex regulatory mechanism, where multiple transcription factors interact combinatorially to...
Yunlong Liu, Matthew P. Vincenti, Hiroki Yokota
ICML
2007
IEEE
14 years 8 months ago
Full regularization path for sparse principal component analysis
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
FGR
2006
IEEE
163views Biometrics» more  FGR 2006»
14 years 1 months ago
Human Action Recognition Using Multi-View Image Sequences Features
Recognizing human action from image sequences is an active area of research in computer vision. In this paper, we present a novel method for human action recognition from image se...
Mohiuddin Ahmad, Seong-Whan Lee