Letters: Linear local tangent space alignment and application to face recognition

Authors:
Tianhao Zhang;Jie Yang;Deli Zhao;Xinliang Ge
Affiliations:
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, P.O. Box A0503221, 800 Dongchuan Road, Shanghai 200240, China;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, P.O. Box A0503221, 800 Dongchuan Road, Shanghai 200240, China;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, P.O. Box A0503221, 800 Dongchuan Road, Shanghai 200240, China;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, P.O. Box A0503221, 800 Dongchuan Road, Shanghai 200240, China
Venue:
Neurocomputing
Year:
2007

Citing 8
Cited 19

Independent component analysis, a new concept?

Signal Processing - Special issue on higher order statistics
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection

IEEE Transactions on Pattern Analysis and Machine Intelligence
The CMU Pose, Illumination, and Expression (PIE) Database

FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Think globally, fit locally: unsupervised learning of low dimensional manifolds

The Journal of Machine Learning Research
Learning a Locality Preserving Subspace for Visual Recognition

ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment

SIAM Journal on Scientific Computing
Neighborhood Preserving Embedding

ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Supervised learning on local tangent space

ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I

Affective interaction based on person-independent facial expression space

Neurocomputing
Letters: Orthogonal discriminant linear local tangent space alignment for face recognition

Neurocomputing
Robust semantic concept detection in large video collections

SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
A two-step framework for highly nonlinear data unfolding

Neurocomputing
Discriminant feature extraction based on center distance

ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Marginal discriminant projections: An adaptable margin discriminant approach to feature reduction and extraction

Pattern Recognition Letters
Orthogonal discriminant local tangent space alignment

ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Orthogonal local spline discriminant projection with application to face recognition

Pattern Recognition Letters
Semi-supervised classification by local coordination

ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Incremental alignment manifold learning

Journal of Computer Science and Technology - Special issue on natural language processing
Front end analysis of speech recognition: a review

International Journal of Speech Technology
Local block representation for face recognition

ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part II
Face recognition using discriminant sparsity neighborhood preserving embedding

Knowledge-Based Systems
Stochastic neighbor projection on manifold for feature extraction

Neurocomputing
Transductive Bayesian regression via manifold learning of prior data structure

Expert Systems with Applications: An International Journal
Maximal Similarity Embedding

Neurocomputing
Learning compact representation for image with tensor manifold perspective

IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Hybrid structure for robust dimensionality reduction

Neurocomputing
Tapkee: an efficient dimension reduction library

The Journal of Machine Learning Research

Quantified Score

Hi-index	0.01

Visualization

Abstract

In this paper, linear local tangent space alignment (LLTSA), as a novel linear dimensionality reduction algorithm, is proposed. It uses the tangent space in the neighborhood of a data point to represent the local geometry, and then aligns those local tangent spaces in the low-dimensional space which is linearly mapped from the raw high-dimensional space. Since images of faces often belong to a manifold of intrinsically low dimension, we develop LLTSA algorithm for effective face manifold learning and recognition. Comprehensive comparisons and extensive experiments show that LLTSA achieves much higher recognition rates than a few competing methods.