Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
A Database for Handwritten Text Recognition Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
Think globally, fit locally: unsupervised learning of low dimensional manifolds
The Journal of Machine Learning Research
Semi-Supervised Learning on Riemannian Manifolds
Machine Learning
Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
SIAM Journal on Scientific Computing
Articulated Structure from Motion by Factorization
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Generalized Principal Component Analysis (GPCA)
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICML '05 Proceedings of the 22nd international conference on Machine learning
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
The Journal of Machine Learning Research
An Algorithm for Finding Intrinsic Dimensionality of Data
IEEE Transactions on Computers
Semi-supervised geodesic Generative Topographic Mapping
Pattern Recognition Letters
An improved local tangent space alignment method for manifold learning
Pattern Recognition Letters
A multi-manifold discriminant analysis method for image feature extraction
Pattern Recognition
Semi-supervised kernel canonical correlation analysis with application to human fMRI
Pattern Recognition Letters
Laplacian Regularized Gaussian Mixture Model for Data Clustering
IEEE Transactions on Knowledge and Data Engineering
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Local and structural consistency for multi-manifold clustering
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Discriminative multi-manifold analysis for face recognition from a single training sample per person
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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Semi-supervised Gaussian mixture model (SGMM) has been successfully applied to a wide range of engineering and scientific fields, including text classification, image retrieval, and biometric identification. Recently, many studies have shown that naturally occurring data may reside on or near manifold structures in ambient space. In this paper, we study the use of SGMM for data sets containing multiple separated or intersecting manifold structures. We propose a new multi-manifold regularized, semi-supervised Gaussian mixture model (M2SGMM) for classifying multiple manifolds. Specifically, we model the data manifold using a similarity graph with local and geometrical consistency properties. The geometrical similarity is measured by a novel application of local tangent space. We regularize the model parameters of the SGMM by incorporating the enhanced Laplacian of the graph. Experiments demonstrate the effectiveness of the proposed approach.