Gait Recognition Using Wavelet Transform

We describe a new method for Automatic Gait Recognition based around the use of wavelet descriptors that model the periodic deformation of human gait. Wavelet descriptors have been used successfully to model the boundary of static or moving, rigid-bodied objects, but many objects actually deform in some way as they move. Here, we use wavelet descriptors to model not only the object’s boundary, but also the spatio-temporal deformations under which the object’s boundary is subjected. We applied this new method to the Large Gait Database, compiled at the University of South Florida (NIST/USF) and found that the wavelet descriptors obtained for each person appear to be unique and can be used for recognition. Successful recognition rates of over 94% were obtained from the Large Gait Database.