A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
Human motion analysis: a review
Computer Vision and Image Understanding
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
Automatic gait recognition by symmetry analysis
Pattern Recognition Letters - Special issue: Audio- and video-based biometric person authentication (AVBPA 2001)
Gait-Based Recognition of Humans Using Continuous HMMs
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Automatic gait recognition using area-based metrics
Pattern Recognition Letters
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
Matching Shape Sequences in Video with Applications in Human Movement Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extraction and temporal segmentation of multiple motion trajectories in human motion
Image and Vision Computing
Level Set Gait Analysis for Synthesis and Reconstruction
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Applications of a simple characterization of human gait in surveillance
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
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We demonstrate a novel approach to modelling arbitrary temporally-deforming objects using spatio-temporal Fourier descriptors. This is a continuous boundary descriptor, which can handle shapes that vary in a periodic manner (such as a walking subject). As such, we can handle non-rigid, moving shapes that self-occlude. We show how this approach has led to successful shape extraction and description with both laboratory-sourced and real-world data. A consequence of exploiting temporal shape correlation in this approach has led to very good tolerance of noise and other positive performance factors. Further to this, our new approach holds sufficient descriptive power not only for extraction, but also for description purposes, and we have been pleased to note high recognition rates in human gait recognition on a large database.