Fage Detect

Project Title

Fage Detect

Project Area of Specialization Artificial IntelligenceProject Summary

Face detection applications use algorithms and ML to find human faces within larger images, which often incorporate other non-face objects such as landscapes, buildings and other human body parts like feet or hands. Face detection algorithms typically start by searching for human eyes -- one of the easiest features to detect. The algorithm might then attempt to detect eyebrows, the mouth, nose, nostrils and the iris. Once the algorithm concludes that it has found a facial region, it applies additional tests to confirm that it has, in fact, detected a face. To help ensure accuracy, the algorithms need to be trained on large data sets incorporating hundreds of thousands of positive and negative images. The training improves the algorithms' ability to determine whether there are faces in an image and where they are.

To ensure or project is able to get the required knowledge from the faces which will be shown to it we will use the very popular AI type used specially for this purpose which is A convolutional neural network (CNN) this is a type of artificial neural network used in image recognition and processing that is specifically designed to process pixel data. An R-CNN generates region proposals on a CNN framework to localize and classify objects in images. Age is an important attribute of identity and social interaction as well for medical processing. Age estimation from the face by intelligent human-machine interfacing is required to capture picture that may contains different parts as well the human face. This proposed application can be used in security, parks, Shopping Malls and swimming pools entrances, and medical clinics. Now in order to understand the working of the project first we need to understand how the project will operate. This project operates on the basis of Computer Vision, it is the field of study that enables computers to see and identify digital images and videos as a human would. The challenges it faces largely follow from the limited understanding of biological vision. Computer Vision involves acquiring, processing, analyzing, and understanding digital images to extract high-dimensional data from the real world.

Project Objectives

Many companies are using these kinds of tools for different purposes making it easier for them to work with customers, cater to their needs better and create a great experience for them. It is easier to identify and predict needs of people based on their gender and age. We want to introduce a mobile app or if being specific we want to give the stores and marketing teams the opportunity to know there customers beforehand and give them the right choice of what do they actually want. This will greatly revolutionize our current way of living not only this it will help the Big and Small brands to help pick the right customer when he or she walks into their shop but will also help customers if a salesmen gives them the right choice of what do they actually want to wear. The software systems of facial recognition analysis usually include several separate neural networks. One of them identifies the person, another one determines the gender, etc. We will try our best to make this purposed solution available to even the low – end devices. As it will be a mobile app so the data we will give to it will be our picture which the software will take into consideration and hence forth give the result as to what the age of the person is and what is it’s gender we will alongside our project also give updates to our current system.

Project Implementation Method

The project is divided in the breakdown structure where first there wil be soem of the Planning involved. After this phase we are going to use Android Studio as our basic IDE to create an android based application which will be further having its develpment in swift for IOS Development or Flutter will be used.

There are After the first phase where we have created the Application we will now use AI based alorithm to teach the face detection of different faces to the Model and use that model in our system. As our application is based on 2 aspects one is live face scanning and other one is upload photot and then scan the Face. So we will implement both of our functions seperatey.

Benefits of the Project

We want to introduce a mobile app or if being specific we want to give the stores and marketing teams the opportunity to know there customers beforehand and give them the right

choice of what do they actually want. This will greatly revolutionize our current way of living not only this it will help the Big and Small brands to help pick the right customer when he or she walks into their shop but will also help customers if a salesmen gives them the right choice of what do they actually want to wear. The software systems of facial recognition analysis usually include several separate neural networks. One of them identifies the person, another one determines the gender, etc. We will try our best to make this purposed solution available to even the low – end devices. As it will be a mobile app so the data we will give to it will be our picture which the software will take into consideration and hence forth give the result as to what the age of the person is and what is it’s gender we will alongside our project also give updates to our current system.

Many companies are using these kinds of tools for different purposes making it easier for them to work with customers, cater to their needs better and create a great experience for them. It is easier to identify and predict needs of people based on their gender and age. We want to introduce a mobile app or if being specific we want to give the stores and marketing teams the opportunity to know there customers beforehand and give them the right choice of what do they actually want. This will greatly revolutionize our current way of living not only this it will help the Big and Small brands to help pick the right customer when he or she walks into their shop but will also help customers if a salesmen gives them the right choice of what do they actually want to wear. The software systems of facial recognition analysis usually include several separate neural networks. One of them identifies the person, another one determines the gender, etc. We will try our best to make this purposed solution available to even the low – end devices. As it will be a mobile app so the data we will give to it will be our picture which the software will take into consideration and hence forth give the result as to what the age of the person is and what is it’s gender we will alongside our project also give updates to our current system.

Technical Details of Final Deliverable

Our Final Deliverable will be having a trained model for gender and age detection we will also be haiving other features added to it such as face mask detection. In order to unloack doors by only seeing to the camera and the criteria that is set for opening the gate if the peron comes on that criteria the door will be automaticaly opened.

Final Deliverable of the Project Software SystemCore Industry ITOther Industries Security Core Technology Artificial Intelligence(AI)Other Technologies Augmented & Virtual RealitySustainable Development Goals Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	30150
Arduino UNO Board	Equipment	2	1000	2000
Motor	Equipment	2	500	1000
Jumper Wires	Equipment	3	400	1200
Bluetooth Chip	Equipment	2	1000	2000
Mini Lights	Equipment	20	20	400
Door Lock	Equipment	2	7000	14000
Prints for Model	Miscellaneous	5	50	250
Print for Documentation	Miscellaneous	3	300	900
Arduino Cable	Equipment	2	200	400
Batteries	Equipment	4	500	2000
Sensors	Equipment	4	1500	6000