A continuous wavelet transform applied to per-joint velocities, followed by a lightweight multi-scale CNN, augments any skeleton backbone with explicit time-frequency dynamics and raises state-of-the-art gait recognition on CASIA-B.
Experimental Settings Datasets.CASIA-B [15] is a widely used multi-view gait dataset comprising 124 subjects recorded from 11 viewpoints (angles0 ◦ to180 ◦ in18 ◦ steps)
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Explicit Time-Frequency Dynamics for Skeleton-Based Gait Recognition
A continuous wavelet transform applied to per-joint velocities, followed by a lightweight multi-scale CNN, augments any skeleton backbone with explicit time-frequency dynamics and raises state-of-the-art gait recognition on CASIA-B.