Small Sample Size Effects in Statistical Pattern Recognition: Recommendations for Practitioners
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Semi-Supervised Learning on Riemannian Manifolds
Machine Learning
Distance-Preserving Projection of High-Dimensional Data for Nonlinear Dimensionality Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simplest Representation Yet for Gait Recognition: Averaged Silhouette
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
The HumanID Gait Challenge Problem: Data Sets, Performance, and Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
SIAM Journal on Scientific Computing
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
Individual Recognition Using Gait Energy Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tensor Discriminant Analysis for View-based Object Recognition
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Graph Embedding and Extensions: A General Framework for Dimensionality Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-isometric manifold learning: analysis and an algorithm
Proceedings of the 24th international conference on Machine learning
Knowledge and Information Systems
General Tensor Discriminant Analysis and Gabor Features for Gait Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Uncorrelated multilinear principal component analysis through successive variance maximization
Proceedings of the 25th international conference on Machine learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Incremental tensor analysis: Theory and applications
ACM Transactions on Knowledge Discovery from Data (TKDD)
Geometric Mean for Subspace Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Patch Alignment for Dimensionality Reduction
IEEE Transactions on Knowledge and Data Engineering
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Supervised locally linear embedding
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Unsupervised learning of image manifolds by semidefinite programming
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Gait Components and Their Application to Gender Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Discriminant Locally Linear Embedding With High-Order Tensor Data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Image Processing
Human Gait Recognition With Matrix Representation
IEEE Transactions on Circuits and Systems for Video Technology
Reconstruction and Recognition of Tensor-Based Objects With Concurrent Subspaces Analysis
IEEE Transactions on Circuits and Systems for Video Technology
Bayesian Tensor Approach for 3-D Face Modeling
IEEE Transactions on Circuits and Systems for Video Technology
Chrono-gait image: a novel temporal template for gait recognition
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
A survey of advances in biometric gait recognition
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Hi-index | 0.00 |
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace without much distorting the pairwise geodesic distances between data points on the Riemannian manifold while preserving discrimination ability. Existing algorithms, e.g., ISOMAP, that try to learn an isometric embedding of data points on a manifold have a nonsatisfactory discrimination ability in practical applications such as face and gait recognition. In this paper, we propose a two-stage algorithm named tensor-based Riemannian manifold distance-approximating projection (TRIMAP), which can quickly compute an approximately optimal projection for a given tensor data set. In the first stage, we construct a graph from labeled or unlabeled data, which correspond to the supervised and unsupervised scenario, respectively, such that we can use the graph distance to obtain an upper bound on an objective function that preserves pairwise geodesic distances. Then, we perform some tensor-based optimization of this upper bound to obtain a projection onto a low-dimensional subspace. In the second stage, we propose three different strategies to enhance the discrimination ability, i.e., make data points from different classes easier to separate and make data points in the same class more compact. Experimental results on two benchmark data sets from the University of South Florida human gait database and the Face Recognition Technology face database show that the discrimination ability of TRIMAP exceeds that of other popular algorithms. We theoretically show that TRIMAP converges. We demonstrate, through experiments on six synthetic data sets, its potential ability to unfold nonlinear manifolds in the first stage.