Gait Recognition Biometric System

As, we enter the digital era, a reliable security system is the need of the hour. Human gait is a unique feature to identify and authenticate a person. Gait has many attractive properties as a biometric, and there are many factors which can confuse the biometric systems. This paper provides the overview of gait analysis, data and factors used in gait and motion analysis, assessment methods, existing gait recognition technologies, how it works and recognizes the gait of a human being, development of a failsafe full proof biometrics using gait analysis, its application in human identification, its advantages over other biometric systems and its limitations which are the concerned topics of research nowadays. This paper proposes a model to efficiently record the selected features of a person’s gait using multiple machine learning algorithms like SVM, NN, K-NN from the video feed and recognize/authenticate the registered personnel via a video input. This paper also refers Hanavan’s model toward the approach for the recognition of a person’s gait. The paper explores various hardware/software requirements such as PyCharm IDE along with additional packages like OpenCV, keras, and Tkinter for the proposed model and analyzes the scope and future prospects of the model.