Gait recognition: An approach based on interval valued features

Gait is one of the biometric traits used to identify an individual by his/her walking style. Gait can be recognized by observing the shape of the body contour variations with time (Spatio-temporal). In this paper, a method of characterizing gait in terms of interval valued type symbolic features is proposed. Axis of least inertia of a shape is exploited to extract symbolic features for gait representation. The proposed representation technique is capable of capturing variations in gait due to change in cloth, carrying a bag and different instances of normal walking conditions more effectively. Experiments are conducted on the standard and considerably large database (CASIA database B) to study the efficacy of the proposed gait recognition system. The proposed method has shown the significant improvements when compared to the state-of-the-art techniques in gait recognition.