Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph Embedded Analysis for Head Pose Estimation
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Graph Embedding and Extensions: A General Framework for Dimensionality Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Regularized locality preserving indexing via spectral regression
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
SRDA: An Efficient Algorithm for Large-Scale Discriminant Analysis
IEEE Transactions on Knowledge and Data Engineering
Person-independent head pose estimation using biased manifold embedding
EURASIP Journal on Advances in Signal Processing
Locating nose-tips and estimating head poses in images by tensorposes
IEEE Transactions on Circuits and Systems for Video Technology
Synchronized submanifold embedding for person-independent pose estimation and beyond
IEEE Transactions on Image Processing
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Spectral regression discriminant analysis (SRDA) is an efficient subspace learning method proposed recently. One important unsolved issue of SRDA is how to automatically determine an appropriate regularization parameter. In this letter, we present a method to estimate the optimal regularization parameter for SRDA. We test our method in different applications including head pose estimation, face recognition, and text categorization. Our extensive experiments evidently illustrate the effectiveness and efficiency of our approach.