Face Recognition is the future Revolution.


Before we dive deep into the topic let's ask a few questions to yourself and start diving into it as deep as you want to…!!!

  1. What it is?
  2. Why it came into existence?
  3. Where it was used?
  4. What are the results we achieve using this?
  5. How we can implement this?


Coming to the journey of this blog that it was a continuous series of six blogs that we are going to discuss about the Facial Recognition in a Feynman Learning Technique, Using CNN and Open CV with Python. Moreover, we need to know brief about the topic.

Technologies Used: Open CV (open source Computer Vision Library) and CNN (Convolutional Neural Networks) Algorithm.

Programming Language used: Python

What it is actually?

Let's suppose two people met at some place at some time on some day...(First Meet)

Person 1: Good morning sir….

Person 2: Good morning. Thanks, May I know, are you?

Person 1:  By the way I’m Kiran new to this apartment.

Person 2: Okay!

Same persons met again after a week – (Next Meet)

Person 1: Hi sir! How are you?

Person 2: Hello, I’m Fine Thanks and What about You?

In the first meet the person came to identify him with some unique identity and then stored in his memory. Where in the second meet he directly recognized the person and greeted him.

This is the same way Face recognizing system is an AI Model that will get trained and will function as a Human in Recognizing the Person. This is happened with series of training of the model and then use. This system led to procure to many applications. Today we are going to dive into the Chapter where to use? And Why it came into existence?

In Technical Terms:

A facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source. There are multiple methods in which facial recognition systems work, but in general, they work by comparing selected facial features from given image with faces within a database. It is also described as a Biometric Artificial Intelligence based application that can uniquely identify a person by analyzing patterns based on the person's facial textures and shapes.  Face Recognition System

Facial Recognition Technology has become a part of Security these days , its applications become enormous in distinct Fields. It will be the world's most used AI technology by 2022.Most of the Applications used this and derived many use cases in the industry , the growth is increasing day by day.

Attendance Management System:

  1. Using this AI Technology People maintain the Attendance records of the employees by identifying the faces in front of the system and matches with the image available in the database to keep their attendance record.
  2. As face recognition technology is one of the least intrusive and fast-growing biometric technologies, it works by identification of People faces using the most unique characteristics of their faces. Say goodbye to proxy Attendance management. Student Attendance Management System


Driver Monitoring System:

  1. The Subaru facial recognition system (Driver Monitoring System), called Driver Focus, stands as the first such biometric platform in the compact SUV segment, Subaru says. Driver Focus aims to reduce the estimated 1,000 injuries per day in the United States that involve distracted driving. The feature will come standard on Forrester’s Touring models, the most expensive Forrester model. Driver Monitoring System
  2. This system monitors the driver's facial expressions and controls the speed of the engine and stops when the driver is tired.


Security Systems:

  1. Companies are fed up with remembering the traditional passwords for accessing, they were training deep learning algorithms to recognize fraud detection, and reduce the need of remembering passwords, and to improve the ability to distinguish between a human face and a photograph.
  2. Gender, age, Liveliness and anti-spoof Detection got included.

Emotion Detecting System:

It’s an Emotion recognition system that which is derived from the face recognition. It identifies the Human emotion and feeling with the expressions on the face. This also came into existence with many applications

Let's check few applications where emotion is a key part of the System:

  1. Buying goods from a shop, whether customer is satisfied or not? We can find this with his facial movements and expressions. Most liked goods can be filtered.
  2. Eating in some restaurants finding the expressions of people whether they are delight full or not? Restaurant Owner can expect the sales of food and improve the order regarding their expressions.
  3. Employee Emotion detection, If the emotion is like frustrated and sad let the system give him a break and make a stress-free environment.


 By-Kranthikiran Diddi


Views: 402

Tags: #AI, #Emotion_Analysis., #Face_Recognition, #ML


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