Letters: Orthogonal tensor rank one differential graph preserving projections with its application to facial expression recognition

Authors:
Shuai Liu;Qiuqi Ruan;Yi Jin
Affiliations:
Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China and Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing 100044, China;Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China and Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing 100044, China;Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China and Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing 100044, China
Venue:
Neurocomputing
Year:
2012

Citing 17
Cited 0

Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection

IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Best Rank-1 and Rank-(R1,R2,. . .,RN) Approximation of Higher-Order Tensors

SIAM Journal on Matrix Analysis and Applications
Coding Facial Expressions with Gabor Wavelets

FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Comprehensive Database for Facial Expression Analysis

FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Manifold of Facial Expression

AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Discriminant Analysis with Tensor Representation

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Neighborhood Preserving Embedding

ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Learning Effective Image Metrics from Few Pairwise Examples

ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
A facial expression recognition system based on supervised locally linear embedding

Pattern Recognition Letters
Graph Embedding and Extensions: A General Framework for Dimensionality Reduction

IEEE Transactions on Pattern Analysis and Machine Intelligence
Tensor Rank One Discriminant Analysis-A convergent method for discriminative multilinear subspace selection

Neurocomputing
Affective interaction based on person-independent facial expression space

Neurocomputing
Extracting the optimal dimensionality for local tensor discriminant analysis

Pattern Recognition
Tensor embedding methods

AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Orthogonal Tensor Neighborhood Preserving Embedding for facial expression recognition

Pattern Recognition
Appearance manifold of facial expression

ICCV'05 Proceedings of the 2005 international conference on Computer Vision in Human-Computer Interaction
Orthogonal Laplacianfaces for Face Recognition

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.01

Visualization

Abstract

In this paper, a new tensor dimensionality reduction algorithm is proposed based on graph preserving criterion and tensor rank-one projections. In the algorithm, a novel, effective and converged orthogonalization process is given based on a differential-form objective function. A set of orthogonal rank-one basis tensors are obtained to preserve the intra-class local manifolds and enhance the inter-class margins. The algorithm is evaluated by applying to the basic facial expressions recognition.