Gait Analysis for Recognition and Classification
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Towards a View Invariant Gait Recognition Algorithm
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
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
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Individual Recognition Using Gait Energy Image
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
Gait recognition for human identification based on ICA and fuzzy SVM through multiple views fusion
Pattern Recognition Letters
Grassmann discriminant analysis: a unifying view on subspace-based learning
Proceedings of the 25th international conference on Machine learning
Computing and evaluating view-normalized body part trajectories
Image and Vision Computing
View-independent human motion classification using image-based reconstruction
Image and Vision Computing
Frame difference energy image for gait recognition with incomplete silhouettes
Pattern Recognition Letters
Kernel Grassmannian distances and discriminant analysis for face recognition from image sets
Pattern Recognition Letters
Locality sensitive discriminant analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Action and gait recognition from recovered 3-D human joints
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
Gait recognition using a view transformation model in the frequency domain
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Graph embedding discriminant analysis on Grassmannian manifolds for improved image set matching
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Set-to-set gait recognition across varying views and walking conditions
ICME '11 Proceedings of the 2011 IEEE International Conference on Multimedia and Expo
| Hi-index | 0.00 |
In studies to date, gait recognition across appearance changes has been a challenging task. In this paper, we present a gait recognition method that models the gait image sets as subspaces on the Grassmannian manifold. This formulation provides a convenient way to represent the subspaces as points on the manifold. By using a suitable Grassmannian kernel, the non-linear manifold can be treated as if it were a Euclidean space. This implies that conventional data analysis tool like LDA can be used on this manifold. To this end, we apply a graph based locality preserving discriminant analysis method on the Grassmannian manifold. Experiment results suggest that the proposed method can tolerate variations in appearance for gait identification.