Can Machines See? Understanding Computer Vision.
Cameras can take pictures by converting light into a two-dimensional array of numbers known as pixels. But these are just lifeless numbers. They do not carry meaning in themselves. Seeing the alphabet of a foreign language does not mean you can read and understand the text. To take pictures is not the same as to see. To truly see means to comprehend and interpret what you’re looking at, not just passively snap a photo like a tourist on vacation.
Computer Vision is a strategy by which machines can understand pictures and videos how they are stored and how we can manipulate them to retrieve useful data from them. It is a subfield of Artificial Intelligence and Machine learning. Computer vision is like the eyes of an AI system, which means if AI enables the machine to think, Computer vision enables the machine to see and observe visual inputs. Understanding the contents of digital images is the main objective of computer vision. But the important question remains, How would a computer see?
Let us understand with an example. At first, it seems quite easy. How hard can it be to describe an object? After all, a cow is just a collection of shapes and colours. This image can easily be detected by a computer by feeding it with a few training images. But what about these cow pictures?
Well, now this seems like a bigger problem. For us humans, it took half a million years to evolve eyes into what we have today, which enables us to identify every single cow picture that we saw above. But this approach again seems impossible for machines. Computers are not the same as humans, they don’t have the gift of vision and perception.
While seeing and perceiving come naturally to humans, that’s not the case with computers. What seemed like a good idea was to give our machines access to all the data that contained millions of pictures all annotated and properly defined so that computers can use it to understand the objects better. This is based on a new statical model called convolutional neural networks (CNN).
Neural networks are somewhat designed to mimic how the human visual system operates. Instead of just telling a computer what the cow looks like we provide it with enormous data in the form of images and let it learn for itself. A CNN assembles a statistical model that learns to associate patterns in images with the correct label. This idea of using big data to train computer algorithms lead to the development of computer vision.
From Blurry to Beautiful: The Impressive Growth of Computer Vision.
Images dominate the internet today. They are everyplace and of all the things that human eyes can see. But with access to this enamours amount of data we also have the computing power to analyze this data. Computer vision is a booming field due to the latest refinements in this field. New hardware and advanced algorithms ensure that the image detection accuracy is high. In less than a decade the improvement in accuracy has gone from 50% to 99%. Making today’s systems more accurate than humans. ln addition to that they are much faster too. It is an accepted fact that computers react much more quickly than humans.
Can you believe that the concept of computer vision dates back to the 1960s?
MIT professor Seymour Papert assigned a group of students a project where they attached a camera to a computer and describe what it saw, sorting the images into “similar objects, similar background areas, and chaos”. This was more than a summer project, as we are still working on it half a century later, this laid the groundwork for what would become one of the fastest-growing and greatly exciting areas of computer science.
How do big tech companies use computer vision?
Apps like Facebook and Instagram use computer vision to detect and filter out to eliminate inappropriate or sensitive content such as nudity, violence, or hate speech. Amazon uses its computer vision technology in its cashier-less store to track customers as they move through the store, by automatically detecting when they pick up or put down items making shopping a breeze. Nvidia is a technology company that specializes in graphics processing units (GPUs), commonly used in computer vision applications. While Tesla uses computer vision in their self-driving cars allowing their Autopilot system to use cameras and sensors to detect obstacles and other vehicles, qualifying the car to drive itself on highways and navigate complex traffic situations.
The Eyes of the Car: The Benefits of Using Computer Vision for Autonomous Navigation.
It is with the help of computer vision that cars and other vehicles can be fully automated. It is used to detect and classify objects (eg. Traffic lights, road signs, and other vehicles), and to create three-dimensional maps or motion estimations. Pretty much every vehicle manufacturer includes semi-autonomous features such as adaptive cruise control, lanes change warnings and assisted steering in their lineups and those are all the same components that will make full self-driving capabilities.
Yet it’s somewhat that is still under development, as despite having various advanced sensors and high-tech cameras, it still has a hard time distinguishing between a harmless paper ball and a perilous rock, they can sometimes be as confused as a chameleon in a bag of Skittles. But fear not, as advancements in computer vision are paving the way for fully automated cars that can distinguish between a paper bag and a boulder with ease. So sit back, relax, and let the computers do the driving — just make sure to hold onto your Skittles!
The End of Passwords: How Fingerprint Recognition is Enhancing Cybersecurity.
If you thought your face was just a pretty picture, think again! With the help of computer vision, your face can now unlock your phone, access your bank account, and even turn you into a cute puppy with just a swipe of a finger. Biometrics has taken security to a whole new level, and computer vision is the superhero behind the mask. But it’s not just about keeping your secrets safe; computer vision also plays a vital role in the fun and games of photo editing apps. Thanks to object detection algorithms, you can now swap faces with your favourite celebrity, add bunny ears to your best friend, or turn your grumpy professor into a pineapple (not recommended). The possibilities are endless
Computer Vision Keeps Traffic Flowing and Defects at Bay!
When it comes to traffic, we all know how frustrating it can be to get stuck in gridlock or end up at a red light that seems to last an eternity. But fear not, because computer vision is here to save the day (and our sanity).
Thanks to this cutting-edge technology, we can now use cameras and AI algorithms to survey the roads and keep traffic flowing smoothly. Computer vision can detect traffic and use that information to regulate traffic lights and maintain traffic regulations. It can even automatically detect pavement degradation to ensure that our roads are safe and well-maintained.
Gone are the days of relying on humans to oversee traffic control systems. With binary operations and lightning-fast processing speeds, computers are now the kings of the road. They can monitor traffic density, track passenger movements, and give drivers real-time updates based on the collected data.
So, the next time you’re stuck in traffic, just remember — computer vision and AI are working tirelessly behind the scenes to keep you safe and keep the traffic flowing. Who knows what other exciting breakthroughs and innovations lie ahead in this exciting field? The road to the future is looking smoother than ever!
The Art of Personalized Style: Using Computer Vision for Fashion Recommendations.
Mirror, mirror on the wall, who’s the most fashionable of them all? Well, with the rise of virtual mirrors, it could be you! These high-tech-looking glasses are not your ordinary mirrors. Equipped with computer vision cameras and augmented reality, they can show you a world of personalized information and enhance your shopping experience like never before.
But it’s not just about flashy technology — these mirrors have substance too. With AI and computer vision, you can virtually try on clothes without worrying about hygiene or damaging the product. It’s like having a fitting room that follows you around!
And if you need a little extra help deciding what to wear, FindMe’s in-store virtual fitting room solution is here to “Complete the Look.” This clever machine-learning engine observes your current outfit and gives you real-time fashion recommendations. So, you can finally achieve that effortless, put-together look without even breaking a sweat. It’s like having your stylist that knows your every fashion whim.
What do we know, what have we learned?
Computers have come a long way in their ability to see and interpret visual data. They can identify objects, recognize faces, and even detect emotions. But let’s face it, they still have a long way to go before they can truly see as we do. For example, while a computer can identify a little girl jumping on a couch, it can’t tell us her name or the reason behind her gleeful leap. It’s like having a detective who can only solve half the mystery.
But don’t lose hope! The future of computer vision and AI is looking bright. Imagine a world where cars are not just automated, but run smarter and safer thanks to machine vision. Where doctors and nurses have an extra pair of tireless eyes to help them diagnose and treat patients. And where robots, not just humans, can brave disaster zones to save lives.
With the help of AI and computer vision, we could even discover new species and resources, and explore unseen frontiers with the help of machines. Who knows what kind of amazing discoveries and innovations lie ahead when we combine the power of human ingenuity with the tireless, analytical capabilities of machines?
So let’s keep pushing the boundaries of computer vision and AI, and see what new marvels we can unlock. The future is looking bright — and we can’t wait to see what it holds!
