Gait recognition using fractal scale
Gait is an identifying biometric feature. Video-based gait recognition has now become a new challenging topic in computer vision. In this paper, fractal scale wavelet analysis is applied to describe and automatically recognize gait. Fractal scale, which is based on wavelet analysis, represents the self-similarity of signals, and improves the flexibility of wavelet moments. It is translation, scale and rotation invariant, and has anti-noise and occlusion handling performance. Moreover, by introducing the Mallat algorithm of wavelet, it reduces the computation complexity. Experiments on three databases show that fractal scale has simple computation and is an efficient descriptor for gait recognition.
gait recognition fractal scale biometric wavelet analysis