THREE D FACE RECOGNITION GLASSES

Project Title

THREE D FACE RECOGNITION GLASSES

Project Area of Specialization Artificial IntelligenceProject Summary

The face is one of the easiest ways to distinguish the individual identity of each other. 
Face recognition is a personal identification system that uses personal characteristics of a 
person to identify the person's identity. Human face recognition procedure basically consists 
of two phases, namely face detection, where this process takes place very rapidly in humans, 
except under conditions where the object is located at a short distance away, the next is the 
introduction, which recognize a face as individuals. Stage is then replicated and developed as 
a model for facial image recognition (face recognition) is one of the much-studied biometrics 
technology and developed by experts. There are two kinds of methods that are currently 
popular in developed face recognition pattern namely, Eigenface method and Fisherface 
method. Facial image recognition Eigenface method is based on the reduction of face-
dimensional space using Principal Component Analysis (PCA) for facial features. The main 
purpose of the use of PCA on face recognition using Eigen faces was formed (face space) by 
finding the eigenvector corresponding to the largest eigenvalue of the face image. The area of 
this project face detection system with face recognition is Image processing. The software 
requirements for this project is matlab software.
Keywords: face detection, Eigen face, PCA, matlab 
Extension: There are vast number of applications from this face detection project, this project 
can be extended that the various parts in the face can be detect which are in various directions

Project Objectives

detection are :
? To design real time face detection system.
 
? To utilize the face detection system based on Haar Classifier.
? To develop face detection system using python
1.3 Work scope
The scopes and guidelines are listed to ensure the research is conducted within its
intended boundary. This is to ensure the research is heading to the right direction to 
achieve its intended objectives.
The first scope of this project is to develop a face detection based on Haar Classifier. 
Haar Classifier is used because it achieved high detection accuracy. Haar Classifier can 
efficiently reduce or increase the class variability and making the classification easier.
The second scope is to extract the human face. It will extract the desire image, for 
this system it will extract human face using Haar Classifier.
 Another scope of this project is used software 
algorithm and show the result. It is used to create face detection system that can detect

Project Implementation Method

the beginning of the 1970's, face recognition was treated as

a 2D pattern recognition problem [2]. The distances between

important points where used to recognize known faces, e.g.

measuring the distance between the eyes or other important

points or measuring different angles of facial components. But

it is necessary that the face recognition systems to be fully

automatic. Face recognition is such a challenging yet

interesting problem that it has attracted researchers who have

different backgrounds: psychology, pattern recognition, neural

networks, computer vision, and computer graphics. The

following methods are used to face recognition.

1. Holistic Matching Methods

2. Feature-based (structural)

Hybrid Methods

Benefits of the Project

Aside from unlocking your smartphone, facial recognition brings other benefits to the companies.

# Enhanced security

The first thing to start with is surveillance. With the help of facial recognition, it will be easier to track down any burglars, thieves, or other trespassers.

On the governmental level, facial recognition can help identify terrorists or any other criminals with the help of the face scan only. The additional bonus is the fact that one cannot hack the technology: there is nothing to steal or change, like in case of a password, for example.

As for personal use, facial recognition can be used as a security tool for locking personal devices and for personal surveillance cameras.

# Faster processing

The process of recognizing a face takes a second or less — and this is incredibly beneficial for the companies.

In the era of constant cyber attacks and advanced hacking tools, companies need a technology that would be both secure and fast. Considering that facial recognition is almost instant, it grants a quick and efficient verification of a person. In addition, it’s hard to fool this technology so this is another bonus.

# Seamless integration

This is probably one of the biggest benefits for companies. The facial recognition technology is quite easily integrated so it’s a perfect choice. It does not require spending additional money on its integration and most facial recognition solutions are compatible with the majority of security software. A 100% win-win.

# Automation of identification

Before, security guards had to perform manual identification of a person that took too much time and did not boast high accuracy. But today, facial recognition is completely independent in the identification process and not only takes seconds but is also incredibly accurate.

The 3D facial recognition technology and the use of infrared cameras significantly boosted the level of accuracy of facial recognition and made it really hard to fool.

Technical Details of Final Deliverable Major milestones in the history of automated face recognition. While the events in the top row highlights the important landmarks in the evolution of face recognition algorithms, those in the bottom row correspond to the turning points in the development of face acquisition systems.  

Source publication

Final Deliverable of the Project Hardware SystemCore Industry SecurityOther Industries IT Core Technology Artificial Intelligence(AI)Other Technologies Artificial Intelligence(AI)Sustainable Development Goals Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	55000
Ressberrypi picamera cable battery hardware memory card	Equipment	1	55000	55000