Gait-based Biometric Identification System using Triangulated Skeletal Models (TSM)

Abstract

Human gait identification is a behavioral biometric technology which can be used to monitor human beings without user interaction. Recent researches are more focused on investigating gait as one of the biometric traits. Further, gait recognition aims to analyze and identify human behavioral activities and may be implemented in different scenarios including access control and criminal analysis. However, using various techniques in relation to image processing and obtaining better accuracy are remaining challenges. In last decade, Microsoft has introduced the Kinect sensor as an innovative sensor to provide image characteristics, precisely. Therefore, this article uses a Kinect sensor to extract gait characteristics to be used in individual recognition. A set of Triangulated shape are generated as new feature vector and called Triangulated Skeletal Model (TSM). Nearest Neighbor technique is utilized to do the recognition issue based on leave-one-out strategy. The experimental outcomes indicated that the recommended technique provides significant results and outperforms other comparative similar techniques with accuracy of 93.46%.