Biometric Technology of the future.

Artificial intelligence:

Intelligence demonstrated by machines is called artificial intelligence. It is presented in the contrast to natural intelligence displayed by human beings. The field of artificial intelligence cover a vast area of human life which are robotics, vision, natural image procession, perception, motion and manipulation, creativity.

Biometrics is the science that studies the human features for anthropometry research, people identification, access control and many more. Biometric features are calculable data classified as physical or behavioral. The previous is related to the body and its shape. Some examples of biometric identities are face recognition system, iris scanner, retina image processing and fingerprint detection system. Face recognition can recognize face features and use face in different emojis and other things to entertain and to manipulate images into different styles.

Characteristics that are associated to human action, for example handwriting and walking is called behavioral characteristics. Intelligent devices used are often expensive.

It valuable to distinguish people through biometric constraints that can be captured and taken at a distance and without the association of the person, such as gait. Kinect is a popular gaming device, that can capture body motion and gestures based on camera and depth sensor. Kinect is able to track in real-time a skeleton model, composed of 20 body joints and save that data.

Many applications examine the gait to notice pathologies of the body movement, reintegration therapy, recognize the fall risk in elderly population to assess the frailty syndrome.

All these applications are based on the study of video and 2D images. Images and videos are managed to collect gait parameters applying both model-based methods, using the characterization of a 3D model of the body in movement, or by model-free methods, that process the silhouette of a walking person.

Using Skeleton Data through different algorithms we can classify people. Skeleton data is used to recognize the gait and other features of human body. Different models of human skeleton were collected for different people and Kinect sensor was placed in between the door. Using Kinect for Windows v1 and the Microsoft SDK different models were selected. People were asked to walk towards and away from camera front view and rare view. Whole module has been divided into different categories according to walking style of person.

Every subject during research contain its own text file in which his gait sequence has been described and collect all his sequence about front, rear, front, rear and so on. This approach of collecting skeleton data using kinetic sensor that a limited set of behavioral features related to the actions of head, elbows and knees is a very up-to-date tool for walking characterization and people recognition.

So, in a way gait recognition system is very effective tool for next upcoming technology. It may be for automatic lock system for doors and houses and many other security and detection system where other biometric like fingerprint, face recognition and other methods are used this is also used and will be implemented in future completely. In some fields like army and others, physical disabilities can also be found using gaits. And in more advancement robots can walk like normal human.

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