Gait recognition by dynamic cues

Many studies have now shown that it is possible to recognize people by the way they walk. As yet there has been little formal study of people recognition using the kinematic-related gait features. We present a new method for gait recognition using dynamic features including the angular measurements of the lower limbs as well as the spatial displacement of the trunk. Gait signatures are derived using a feature selection algorithm which is based on a validation-criterion. We show that gait angular measurements derived from the joint motions mainly the ankle, knee and hip angles, possess most of the discriminatory potency for gait recognition with an achieved correct classification rate of 95.7%.

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