Human Gait Recognition Using Fuzzy Logic

Abstract

In this paper, an efficient technique has been implemented for gait based human identification. This paper proposes a human identification system based on human gait signatures extracted using topological analysis and properties of body segments. The gait features extracted are height, hip, neck and knee of the human silhouette and a model-based feature i.e. area under hermite curve of hip and knees. The experimental phase has been conducted on the SOTON covariate database, which comprises of eleven subjects. The database also takes into account different factors that vary in terms of apparel, carrying objects etc. Subject classification is performed using fuzzy logic and compared against the nearest neighbor method. From the conducted experimental results, it can be accomplished that the stated approach is successful in human identification while some analysis prove that specific number of input variables and membership functions help to elevate the accuracy level.