Gait Recognition for Human Identification Using Higher Order Shape Configuration

Prof. Sunita P. Aware, Dr. Chetan M. Sedani


This paper put forward Different from gait classification which classifies human motion into categories, such as walking, running, and jumping, gait recognition, also called gait-based human identification, is a relatively new research direction in biometrics. It aims to discriminate individuals by the way they walk. In comparison with other first-generation biometric features such as fingerprint and iris, gait has the advantage of being unobtrusive, i.e., it requires no subject. Human identification at a distance has recently gained growing interest from computer vision researchers. Gait recognition aims essentially to address this problem by identifying people based on the way they walk. In this paper, a simple but efficient gait recognition algorithm using Higher Order Shape Configuration Gait has been known as an effective biometric feature to identify a person at a distance. However, variation of walking speeds may lead to significant changes to human walking patterns. It causes many difficulties for gait recognition. A comprehensive analysis has been carried out in this paper to identify such effects. Based on the analysis, Procrustes shape analysis is adopted for gait signature description and relevant similarity measurement.

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