Human identification can be enhanced by biometric features such as fingerprints, retina, palm, voice recognition, and gait recognition (Jain et al. in Handbook of biometrics. Springer Science & Business Media, 2007.). Most of these require the subject’s permission and physical attention. However, human gait recognition works by analyzing the gait of walking subjects to identify individuals without their awareness or consent (Nixon et al. in Human identification based on gait, vol 4. Springer Science & Business Media, 2010; Goffredo et al. in Multimedia Tools and Applications 50:75–94, 2010). This paper discusses a human gait recognition system applied to the Outdoor Gait dataset and CASIA-C dataset, achieving recognition rates of 96% and 97.7% respectively (Zheng et al. in IEEE 2011:2073–2076, 2011; Muramatsu et al. in IEEE Transactions on Cybernetics 46:1602–1615, 2015).