Gait recognition based on vision systems: A systematic survey

Abstract

With the growing popularity of biometrics technology in the pattern recognition field, especiallyidentification of human has gained the attention of researchers from both academia and industry. One such type of biometric technique is Gait recognition, which is used to identify a human being based on their walking style. Generally, two types of approaches are adopted by any algorithm designed for gait recognition, namely model based and model free approaches. The key reason behind the popularity of gait recognition is that it can identify a person from a considerable distance while other biometrics has failed to do so. In this paper, the authors have conducted a survey of extant studies on gait recognition in consideration of gait recognition approaches and phases of a gait cycle. Moreover, some aspects like floor sensors, accelerometer based recognition, the influences of environmental factors, which are ignored by exiting surveys, are also covered in our survey study. The information of gait is usually obtained from different parts of silhouettes. This paper also describes different benchmark datasets for gait recognition. This study will provide firsthand knowledge to the researchers working on the gait recognition domain in any real-world field. It has been observed that work done on the gait recognition with sufficiently high accuracy is limited in comparison to research on various other biometric recognition systems and has enough potential for future research.