Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance Evaluation of the Nearest Feature Line Method in Image Classification and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discriminant Waveletfaces and Nearest Feature Classifiers for Face Recognition
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
On Modeling Variations for Face Authentication
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
The Journal of Machine Learning Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Discriminant Embedding and Its Variants
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Where Are Linear Feature Extraction Methods Applicable?
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph Embedding and Extensions: A General Framework for Dimensionality Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rectified nearest feature line segment for pattern classification
Pattern Recognition
Locality preserving CCA with applications to data visualization and pose estimation
Image and Vision Computing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Correlation Metric for Generalized Feature Extraction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Locality sensitive discriminant analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A novel classifier based on shortest feature line segment
Pattern Recognition Letters
Clustering appearances of objects under varying illumination conditions
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Face Recognition Using Nearest Feature Space Embedding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition using the nearest feature line method
IEEE Transactions on Neural Networks
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Shortest feature line segment (SFLS) is a recently proposed classification approach based on nearest feature line (NFL). It naturally inherits the representational capacity enlargement property of NFL and offers many other benefits in accuracy and efficiency. However, SFLS still has several drawbacks, limiting its generalization ability. In this paper, we develop a manifold learning algorithm for dimensionality reduction based on a novel line-based metric derived by integrating SFLS and NFL, which takes advantage of the benefits of the two algorithms and avoids their disadvantages. Unlike the construction of a point-based relationship in traditional dimensionality reduction algorithms, the new measurement forms linear models of multiple feature points, which capture more information than individual prototype and serve to discover the intrinsic connection of nearby points. Moreover, to enhance the discriminating capability, the affinity matrix in graph embedding is designed in supervised manner by using class label information. Experimental results on four standard databases for face recognition confirm the effectiveness of our proposed method.