Human Recognition by GAIT

Project Title

Human Recognition by GAIT

Project Area of Specialization Artificial IntelligenceProject Summary

GAIT refers to the style of walking of an individual. Often, in surveillance applications, it is difficult to get face or iris information at the resolution required for recognition. Studies in psychophysics indicates thay humans have capability of recognizing people from even impoverished displays of gait,indicating the presence of identity information in gait. From early medical studies, it appears that there are 24 different components in human gait, and that if all, the measurements are considered, gait is unique. It is interesting, therefore, to study the utility of gait as a biometric. A gait cycle corresponds to one complete cycle from rest (standing) position to-right-foot-forward-to-rest-to-left-foot-forward-to-rest-position. The movements within the cycle consists of the motion of the different parts of the body such as head, hands, legs etc. The characteristics of an individual are reflected not only in the dynamics and the periodicity if a gait cycle but also in the height and width of that individual.

Project Objectives

The main objective of this project is to: 1. Develop a program capable of performing recognition of individuals derived from a video sequence of a person walking. The program should be able to store the derived gait signature for comparison at a later stage. Automatic extraction of relevant gait feature points should be available from a video sequence in order to automate the classification process. 

The project can then be broken down into three main sections, which were completed in the following order:  

• Recognition Engine – develop the algorithms and functionality that can classify individuals based on extracted gait information.

 • Segmentation – extract the foreground subjects from the video sequence, ready for extracting gait features.

 • Feature Extraction – the segmented image map is used to extract the relevant gait features which will be used for classification.

Project Implementation Method

The codes will run on the NVIDIA Jetson TX2 Module because it is a powerful microprocessor which can run the gait recognition and pose estimation on a camera feed with good frames per second (fps). The gait recognition neural networks were trained on a Core i7 9th Gen. PC with NVIDIA Geforce GTX 1660 Ti.

Benefits of the Project

Biometric systems for human identification at distance have ever been an increasing demand in various significant applications. Many biometric resources, for instance iris, fingerprint, palmprint, hand geometry have been systematically studied and employed in many systems. In spite of their widespread applications, these resources suffer from two main disadvantages: 1) Failure to match in low resolution images, pictures taken at a distance and 2) Necessitates user cooperation for accurate results. For these reasons, innovative biometric recognition methods for human identification at a distance have been an urgent need for surveillance applications and gained immense attention among the computer vision community researchers in recent years. In this modern era, the integration of human motion analysis and biometrics has fascinated several security-sensitive environments such as military, banks, parks and airports etc and has turned out to be a popular research direction. Human gait recognition works from the observation that an individual’s walking style is unique and can be used for human identification. So as to recognize individual’s walking characteristics, gait recognition includes visual cue extraction as well as classification. But the major issue here is the representation of the gait features in an efficient manner.

Technical Details of Final Deliverable

The final deliverable will be a NVIDIA Jetson TX2 Module running the gait recognition and pose estimation codes, using the video feed from an IP Camera.

Final Deliverable of the Project HW/SW integrated systemCore Industry SecurityOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Industry, Innovation and Infrastructure, Peace and Justice Strong InstitutionsRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	70000
Nvidia Jetson TX 2 Module	Equipment	1	70000	70000