The prime objective of this paper is to comprehend the human gait in biometric and biomedical applications. Human gait recognition is recognizing people from the manner in which they walk. It is identified with acquiring biometric data, for example, identity, gender, ethnicity and age from people walking patterns. Likewise, biomedical data can be acquired like individual`s illness, body abnormality. In the walking process, the human body shows general periodic motion, particularly upper and lower limbs, which reflect the person`s unique movement pattern. Contrasted with different biometrics modalities, gait can be acquired from distance and is hard to hide and camouflage. Gait has been topic in PC vision with extraordinary advancement accomplished in ongoing ten years. In this paper, we give a survey over state-of-art gait innovation; focus on different factors in gait methodology and ongoing advances in biomedical engineering.

Human gait, Gait recognition, Biometrics, Biomedical

[1] R. D. Green and L. Guan, “Quantifying and Recognizing Human Movement Patterns from Monocular Video Im-ages-Part II: Applications to Biometrics,” IEEE Transac-tions on Circuits Systems for Video Technology, Vol. 14, No. 2, 2004, pp. 191-198.
[2] Davrondzhon Gafurov., A Survey of Biometric Gait Recognition: Approaches, Security and Challenges, NIK-2007 conference.
[3] L. Wang, H. Z. Ning, T. N. Tan and W. M. Hu, “Fusion of Static and Dynamic Body Biometrics for Gait Recog-nition,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 14, No. 2, 2004, pp. 149-158.
[4] Bobick, A., Johnson, A.: Gait recognitin using static activity-specific parameters. In: Computer Vision and Pattern Recognition 2001. Volume I., Kauai, HI(2001).
[5] J. B. dec. M. Saunders, V. T. Inman and H. D. Eberhart, “The Major Determinants in Normal and Pathological Gait,” The Journal of Bone and Joint Surgery, Vol. 35-A, No. 3, 1953, pp. 543-558.
[6] Jeffrey E. Boyd, James J. Little, “Biometric Gait Recognition”, Springer-Verlag Berlin Heidelberg, pp. 19–42, 2005
[7] M. Hofmann and G. Rigoll, "Improved Gait Recognition using Gradient Histogram Energy Image," 2012 19th IEEE International Conference on Image Processing, Orlando, FL, 2012, pp. 1389-1392.
[8] E. Hossain and G. Chetty, "A multi-modal gait based human identity recognition system based on surveillance videos," 2012 6th International Conference on Signal Processing and Communication Systems, Gold Coast, QLD, 2012, pp. 1-4.
[9] S. Gabriel-Sanz, R. Vera-Rodriguez, P. Tome and J. Fierrez, "Assessment of gait recognition based on the lower part of the human body," 2013 International Workshop on Biometrics and Forensics (IWBF), Lisbon, 2013, pp. 1-4.
[10] A. O. Lishani, L. Boubchir and A. Bouridane, "Haralick features for GEI-based human gait recognition," 2014 26th International Conference on Microelectronics (ICM), Doha, 2014, pp. 36-39.
[11] S. C. Bakchy, M. R. Islam and A. Sayeed, "Human identification on the basis of gait analysis using Kohonen self-organizing mapping technique," 2016 2nd International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE), Rajshahi, 2016, pp. 1-4.
[12] W. G. Bhargavas, K. Harshavardhan, G. C. Mohan, A. N. Sharma and C. Prathap, "Human identification using gait recognition," 2017 International Conference on Communication and Signal Processing (ICCSP), Chennai, 2017, pp. 1510-1513.
[13] Z. Wu, Y. Huang, L. Wang, X. Wang and T. Tan, "A Comprehensive Study on Cross-View Gait Based Human Identification with Deep CNNs," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 2, pp. 209-226, 1 Feb. 2017.