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…!!!
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
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.
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: