Moving object recognition in eigenspace representation: gait analysis and lip reading
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multi-view Method for Gait Recognition Using Static Body Parameters
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Gait Analysis for Recognition and Classification
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Extracting Human Gait Signatures by Body Segment Properties
SSIAI '02 Proceedings of the Fifth IEEE Southwest Symposium on Image Analysis and Interpretation
The HumanID Gait Challenge Problem: Data Sets, Performance, and Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gait recognition using linear time normalization
Pattern Recognition
Effect of silhouette quality on hard problems in gait recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A full-body layered deformable model for automatic model-based gait recognition
EURASIP Journal on Advances in Signal Processing
Gait Recognition Based on Silhouette, Contour and Classifier Ensembles
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Gait recognition based on time-frequency analysis
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
A macro-observation scheme for abnormal event detection in daily-life video sequences
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
Ongoing human action recognition with motion capture
Pattern Recognition
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This paper presents a novel approach for gait recognition based on the matching of body components. The human body components are studied separately and are shown to have unequal discrimination power. Several approaches are presented for the combination of the results obtained from different body components into a common distance metric for the evaluation of similarity between gait sequences. A method is also proposed for the determination of the weighting of the various body components based on their contribution to recognition performance. Using the best performing of the proposed methods, improved recognition performance is achieved.