A Comprehensive Review of the Occlusion Identification Based Gait Recognition Mechanism

Abstract

This pattern module of gait has been developed by the capturing process of a scene of obj ects during the walking cycle of subjects, but in the case of a populated or multi-person environment, the region of interest or subject is often obstructed by the numerous static and dynamic obj ects. Due to the obstruction (process of occlusion), the information developed by the gait pattern model has been discarded or lost. This process of obstruction of the subject due to several environmental objects during the development of the gait pattern is known as occlusion. Numerous techniques, including Lagrange's inter-polation, piece-wise cubic hermite interpolation, spline inter-polation, periodic curve fitting, linear curve fitting, and quadratic curve fitting, were applied in the reconstruction of these hidden sequences of the pattern gait module. This work provides an introduction to the mechanisms involved in occluded-based gait reconstruction and explores the difficulties encountered in trying to describe this system. This paper also describes the literature reported by numerous researchers over the past few years. The primary goal of this paper is to provide a comprehensive review of the current methods for recovering occluded gait patterns based on research.