Have you noticed how certain popular social media platforms have gained an odd capacity to recognize your pals in your photos? Previously, you were compelled to tag your friends on images by clicking on them and inputting their names. They now automatically tag everyone for you when you upload a photo.
Facial recognition is the name given to this technology. The algorithms on social media may recognize your friends’ faces after only a few times being tagged. It’s incredible technology, and these social media platforms can recognize faces with 98 percent accuracy, which is about as good as humans can get!
Let’s have a look at how current facial recognition functions. Continue reading to find out all you need to know about why you should try Imarticus iit artificial intelligence course, Artificial intelligence and machine learning course and the Best Machine Learning & AI Course.
How to use machine learning on Modern face recognition
Facial recognition is actually a collection of related issues. To begin, locate all of the faces in a picture. Second, concentrate on each face and be able to recognize that it is still the same person even if it is turned in an unusual way or lit poorly. Third, be able to identify distinct elements of a person’s face that may be used to distinguish them from others, such as eye size, facial length, and so on. Last, identify the person’s name by comparing the distinctive qualities of this face to all of the persons you already know.
Because computers can’t accomplish this type of high-level generalization (at least not yet…), you’ll have to educate them how to do each stage of the process individually. You must create a pipeline in which each phase of face recognition is solved individually and the result is passed on.
Facial recognition – step by step
- Step 1: Find all the faces:
Face detection is the initial phase in your process. Obviously, before we can try to discern the faces in a snapshot, you must first locate them! You’ve probably seen face detection in action if you’ve used a camera in the previous ten years.
- Step 2: Laying and projecting faces
Once you’ve separated the faces in your image, you’ll have to deal with the fact that faces facing in various orientations seem to a computer in completely different ways.
- Step 3: Encoding the faces
You’ve arrived to the crux of the issue: identifying the faces. This is when things start to get exciting! The most straightforward method of facial recognition is to compare the unknown face you discovered in step 2 to all of the photographs you have of people who have previously been tagged. It must be the same person if you uncover a previously tagged face that appears quite similar to our unknown face. Doesn’t it sound like a great idea?
- Step 4: Finding the person’s name from the encoding
This final step is actually the easiest of the entire procedure. All you have to do now is look through your database of known persons to discover the person with the most similar dimensions to our test image. Any simple machine learning classification algorithm would suffice. No advanced deep learning techniques are required.
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