Abstract:

The goal of this study is to identify people using gait. This understanding is predicated on the idea that each person has a distinctive walking style, which may include variations in step length, hip angle, foot angle, and other intrinsic and extrinsic traits. Biometric techniques such as fingerprint, iris, and face identification require the physical attention of humans, in contrast to gait recognition, which can certify persons in a relatively short amount of time. [1]. For instance, gait recognition uses a person's gait to swiftly, accurately, and without the help of a human, while fingerprint recognition uses a person's fingerprints to distinguish one person from another. It develops solutions with excellent security, precision, and 3D recognition capabilities.[2]. With the development of computer vision capabilities, one less popular but very reliable biometric identification method is called "gait recognition," which uses a subject's walking pattern to identify them. There are many other ways to identify a person. Several source or capture devices, such as video cameras, motion sensors, and other tools, can be used to distinguish people even when they are far away. [4]. This can be accomplished by identifying the subject from the video frame, utilising silhouette segments from the video sequence to extract the pertinent features, and then classifying the outcomes using the database

Description:

Gait recognition, Biometrics, security, silhouette segments, feature extraction, Walking pattern, classification, Human identification