17 search results - page 2 / 4 » Non-linear feature extraction by linear PCA using local kern... |
PSIVT
2009
Springer
13 years 11 months ago
2009
Springer
PCA-SIFT is an extension to SIFT which aims to reduce SIFT’s high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminati...
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
This paper presents a new approach to feature analysis in automatic speech recognition (ASR) based on locality preserving projections (LPP). LPP is a manifold based dimensionality...
AMFG
2007
IEEE
13 years 10 months ago
2007
IEEE
Extending recognition to uncontrolled situations is a key challenge for practical face recognition systems. Finding efficient and discriminative facial appearance descriptors is c...
SCALESPACE
2007
Springer
13 years 10 months ago
2007
Springer
Abstract. Natural images consist of texture, structure and smooth regions and this makes the task of filtering challenging mainly when it aims at edge and texture preservation. In...
PAMI
2012
11 years 7 months ago
2012
— Over the last century, Component Analysis (CA) methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Lap...