Gait recognition of different people groups based on Fourier descriptor and support vector machine

In this paper, we present a novel method for gait recognition of different people groups based on Fourier descriptors (FDs) and support vector machine (SVM). The proposed method involves the procedures of background modeling, extraction of gait silhouettes by background subtraction, shadow removal, representation of gait silhouettes using the FDs, and recognition of human gaits by an SVM Classifier. To evaluate the performance of the proposed method, 5 different people groups with 15 video sequences, including the pregnant, the children, the adult, the people with a walking stick, and the aged, are utilized. Experimental results show that the correct recognition rate (CRR) of 81% is obtained using only the first 20 coefficients of FDs, indicating the feasibility of the proposed method.