Document Type
Article
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
2. ENGINEERING AND TECHNOLOGY
Abstract
Human gait recognition system identifies individuals based on their biometric traits. A human’s biometric features can be grouped into physiologic or behavioral traits. Biometric traits, such as the face [1], ears [2], iris [3], finger prints, passwords, and tokens, require highly accurate recognition and a well-controlled human interaction to be effective. In contrast, behavioral traits such as voice, signature, and gait do not require any human interaction and can be collected in a hidden and non-invasive mode with a camera system at a low resolution. In comparison with other physiological traits, one of the main advantages of gait analysis is the collection of data from a certain distance. However, gait is less powerful than physiological traits, yet it still has widespread application in surveillance for unfavorable situations. From traditional algorithms to deep learning models, a gait survey provides a detailed history of gait recognition.
DOI
https://doi.org/10.1016/j.rineng.2022.100556
Recommended Citation
Asif, M., Tiwana, M.I. & Khan, U.S. (2022). Human gait recognition subject to different covariate factors in a multi-view environment. Results in Engineering, vol. 15, pg. 100556 doi:10.1016/j.rineng.2022.100556