A global human walking model with real-time kinematic personification
The Visual Computer: International Journal of Computer Graphics - Special issue on computer animation 1989/90
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AIPR '05 Proceedings of the 34th Applied Imagery and Pattern Recognition Workshop
Multiple window spectrogram and time-frequency distributions
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A method for time-frequency analysis
IEEE Transactions on Signal Processing
Multiwindow time-varying spectrum with instantaneous bandwidth andfrequency constraints
IEEE Transactions on Signal Processing
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We introduce a new and simple technique for human gait classification based on the time-frequency analysis of radar data. The focus is on the classification of arm movements to discern free vs. confined arm swinging motion. The latter may arise in hostage situation or may be indicative to carrying objects with one or both hands. The motion signatures corresponding to the arm and leg movements are both extracted from the time-frequency representation of the micro-Doppler. The time-frequency analysis is performed using the multiwindow S-method. With the Hermite functions acting as multiwindows, it is shown that the Hermite S-method provides an efficient representation of the complex Doppler associated with human walking. The proposed human gait classification technique utilizes the arm positive and negative Doppler frequencies and their relative time of occurrence. It is tested on various real radar signals and shown to provide an accurate classification.