The visual analysis of human movement: a survey
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Recognition of Human Movement Using Temporal Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic extraction and description of human gait models for recognition purposes
Computer Vision and Image Understanding
Stride and Cadence as a Biometric in Automatic Person Identification and Verification
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Silhouette Analysis-Based Gait Recognition for Human Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
The HumanID Gait Challenge Problem: Data Sets, Performance, and Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Individual Recognition Using Gait Energy Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multimodal biometrics using geometry preserving projections
Pattern Recognition
General Tensor Discriminant Analysis and Gabor Features for Gait Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric Mean for Subspace Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Transductive Component Analysis
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Automatic gait recognition via Fourier descriptors of deformable objects
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
On automated model-based extraction and analysis of gait
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Advances in automatic gait recognition
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture 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
Statistical motion model based on the change of feature relationships: human gait-based recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Identification of humans using gait
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
A multiresolution approach to computer verification of handwritten signatures
IEEE Transactions on Image Processing
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In this paper, we propose a new gait recognition method using recursive spatiotemporal subspace learning. In the first stage, periodic dynamic feature of gait over time is extracted by Principal Component Analysis (PCA) and gait sequences are represented in the form of Periodicity Feature Vector (PFV). In the second stage, shape feature of gait over space is extracted by Discriminative Locality Alignment (DLA) based on the PFV representation of gait sequences. After the recursive subspace learning, gait sequence data is compressed into a very compact vector named Gait Feature Vector (GFV) which is used for individual recognition. Compared to other gait recognition methods, GFV is an effective representation of gait because the recursive spatiotemporal subspace learning technique extracts both the shape features and the dynamic features. And at the same time, representing gait sequences in PFV form is an efficient way to save storage space and computational time. Experimental result shows that the proposed method achieves highly competitive performance with respect to the published gait recognition approaches on the USF HumanID gait database.