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» A Subspace Kernel for Nonlinear Feature Extraction
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ICPR
2010
IEEE
13 years 4 months ago
Improving Classification Accuracy by Comparing Local Features through Canonical Correlations
Classifying images using features extracted from densely sampled local patches has enjoyed significant success in many detection and recognition tasks. It is also well known that ...
Mert Dikmen, Thomas S. Huang
CVPR
2009
IEEE
1962views Computer Vision» more  CVPR 2009»
15 years 1 months ago
Histograms of Oriented Optical Flow and Binet-Cauchy Kernels on Nonlinear Dynamical Systems for the Recognition of Human Actions
System theoretic approaches to action recognition model the dynamics of a scene with linear dynamical systems (LDSs) and perform classification using metrics on the space of LDSs, ...
Rizwan Chaudhry, Avinash Ravichandran, Gregory D. ...
ICASSP
2008
IEEE
14 years 1 months ago
A study of using locality preserving projections for feature extraction in speech recognition
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...
Yun Tang, Richard Rose
ICPR
2008
IEEE
14 years 1 months ago
Online anomal movement detection based on unsupervised incremental learning
We propose an online anomal movement detection method using incremental unsupervised learning. As the feature for discrimination, we extract the principal component of the spatio-...
Kyoko Sudo, Tatsuya Osawa, Hidenori Tanaka, Hideki...
ICB
2007
Springer
176views Biometrics» more  ICB 2007»
13 years 10 months ago
A Novel Null Space-Based Kernel Discriminant Analysis for Face Recognition
The symmetrical decomposition is a powerful method to extract features for image recognition. It reveals the significant discriminative information from the mirror image of symmetr...
Tuo Zhao, Zhizheng Liang, David Zhang, Yahui Liu