What is Computer Vision? Why It’s Taking Over Your Tech Life

The term "computer vision" is quite futuristic; we are talking of cyborg eyes or something Black Mirror-esque, if you will. Almost form of the literal sense, it cannot be awfully far from that definition. Already living amongst us, it is probably a way deeper aspect of life than many would think.

Here we will elaborate on what actually constitutes computer vision, how it emerged, and what significance it retains today, and how you would fit into it, especially as a student trying to figure it all out or a professional looking to elevate himself. 

What Is Computer Vision?

In basic terms, computer vision is the one, which helps the machine to "see" and comprehend things around it, just like us, except through a computer screen and lots of equations. It is a subfield of artificial intelligence (AI) that deals with image and video analysis: you must have seen it at work every time your phone unlocks via Face ID or whenever your photo app detects your face in an album on your phone.

Now, suppose an explanation of a dog to a little kid. You would show the kid tons of pictures, saying, "This is a dog." After enough repetitions, the kid would get it. In the same spirit, we feed the computers zillions of images and then let the computers learn the patterns. After countless repetitions, they become very good at telling what is what.

Computer Vision; A Quick History

Computer vision isn't hypothetical; it has been around since the 1960s. Initially, during this period, they were busy teaching machines to recognize simple shapes: blocks and lines.

From about the '90s onward, when hardware and algorithms started getting well, it went off like a rocket. Enter deep learning in the 2010s-a real game-changer-and machines were suddenly recognizing cats, humans, products, traffic signs, and tumors. The history of computer vision is basically a tech class glow-up story.

How Does It Actually Work? 

Computer vision is a code-brain of sorts. Everything behind the curtain is an orchestra of algorithms, techniques, and models; learning patterns, pixel by pixel, through the process of looking. The great computer vision tech is, of course, based on neural networks, especially convolutional neural networks, the secret sauce of computer vision. Want to teach pizza recognition? Then you must put in thousands of images of pizzas. In the end, it should be able to determine what constitutes pizza: cheese, tomato, and dough. Not perfectly, but thereabouts within the scary range."

Why Should You Care?

Computer vision is no longer a lab-animal to be experimented on; live presentations are already showing it to be useful. For students, it widens the doors into AI and technology that is frankly exciting and meaningful. For working professionals? It’s a market-up. Having computer vision skills is an extra, especially as industries hit the full gas in automation and data.

Think of doctors earlier detecting diseases using it, self-driving cars using it to avert accidents, retail stores keeping a tab on footfall and stocks with zero human input. It’s smart tech making our lives smooth and safe.

Are You Already Using Computer Vision?

If you're on Snapchat or Instagram, computer vision has been placed in your hands. These face filters detect where your eyes and nose are: yes. Google Photos sorting pictures for you? Another case of computer vision. The scanning app for your assignments? You've guessed it.

And that's not all for fun! Supermarkets use it for inventory. Airports use it for security. Farmers are using drones along with CV software to track the health of their crops. Basically, it's everywhere, silently doing its own thing in the background. 

The Tools: Computer Vision Software Making It Happen

Magic can't happen without tools. Well, computer vision software happens to be one prime support there. Very nice and very respected tools include OpenCV (the starter pack for anyone with curiosity), TensorFlow, and PyTorch. Off-campus, cloud computing solutions like Amazon Recognition take this on-neat.

More interestingly, a good number of these tools are open source. For students with a laptop and Wi-Fi, you're good to go in getting your feet wet. Build face detectors, build filter apps, experiment with object tracking, and others.

Computer Vision Just Isn'T There Yet

Computer vision needs massively huge data. And if the data is biased, the results are biased too. Like, facial recognition software sometimes struggles with diversity. A very big problem. Another related problem is privacy. Like, do you want a system to track your every move?

But the good thing is that these are already known issues. Researchers and developers are doing their best to make it more ethical and inclusive. So, it’s a work in progress and is heading toward the right place. 

Should You Learn Computer Vision?

What makes the moment exciting to pursue computer vision? Because it is growing and is definitely futuristic. It's amazing for anyone interested in working to promote a product, improve data, focus on UX, develop healthcare tech, or just want to figure out how these amazing tools really work-understanding CV gives one a leg-up to start.

Not that you must be a programmer right on the first day. You can start little, remain inquisitive, and build something interesting along the way, if only for the fun of it. The job market embraces it, and it's really awesome knowing the figures in which the machines are "learning to see". What it is about computer vision, is that it is everywhere right now. Be it a pursuit of a career in product, data, UX, health tech, or even an urge to think smart about the work to create is what gives CV a tough start ahead.

You do not need to be a coder from day 1. Start slow, be inquisitive, and maybe build something fun along the way. The job market loves it, and it feels good to know what it is like for machines to be learning how to "see".

What’s Next?

If you're dreaming of a career in computer vision, here’s your sign to go for it. At PW IOI School of Technology, you can kickstart your journey with a B.Tech program that’s designed for the future and here you will learn all the related concepts that will help you further to up-skill in computer vision. From coding to AI and everything in between, you’ll learn it all. It’s smart, practical, and built for students who want to make a real impact.