Computer Vision: What Areas Does It Affect?

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This article was written by guest contributor Andrew Mikhailov. For more information about Andrew, check out the links at the end of this article.

Is it an eye with AI? In a way.

More fully, computer vision is a form of artificial intelligence that lets computers identify things and extract a high-level understanding of the visual world. This is not just a machine seeing an object, but also processing the data so that the observations provide useful information. The supreme aim of computer vision is to make decisions based on image analysis.

For long, AI-based solutions had resided in tech labs as part of the research and sophisticated computing projects. Now they are entering the business and real consumer market like wildfire.

Computer vision is used in drones, face recognition, autonomous vehicles, and robots. The applications of computer vision are so diverse that it is tough to think of a business that couldn’t benefit from it. According to a Market research store, the Computer vision market is expanding at a rate of nearly 50% a year and anticipated to reach $25 billion by 2023.

What areas benefit from Computer vision most? Let’s take the plunge to see.

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Computer vision is powered by deep learning. The reason is those deep learning methods can leverage massive datasets of faces and learn their rich representation, allowing modern models to perform and later even to outperform the face recognition capabilities of humans. This technology indeed delivers superhuman performance and high accuracy of output results.

Many companies have leveraged from the pros of AI and face recognition in particular.

Facebook made the first introduction to the advancement and accuracy of facial recognition. They use this technology to tag faces in photos posted in a profile if the user allows it.

Another example is Apple. With a glance, Face recognition unlocks iPhone or iPad Pro. This technology can be used to authorize purchases from App Store and Apple Books and payments with Apple Pay.

Microsoft has recently launched the Seeing AI app for visually impaired and blind people to narrate the world around them. It can tell them what is in front of them and recognize the faces of the surrounding people.

Amazon presents a revolutionary concept. They unveiled 26 AmazonGo stores where shoppers can avoid lines and pay for items right away. Customers even don’t need to use a self-checkout station — the ceiling of the store has cameras, and store shelves have weight sensors to detect which items a customer took. The system places them in the virtual cart.

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Armed with computer vision algorithms and optical sensors for localization in the environment, vision-based navigation revs fast.

Its recent growth spurt owes to several drivers: falling sensor prices, open-source development, rapid prototyping opportunities with 3D printers, and the ubiquity of IoT devices. As a result, automation is increasing in industries like automotive, electronics manufacturing, and order fulfillment warehouses.

Modern robotic solutions consist of combining a 3D camera with software. It allows detecting the position, orientation, and dimensions of objects so that a robot gripper can pick and place items quickly and accurately.

Many industrial manufacturing businesses have installed automated robotic arms to help create products for vehicles and their parts, etc. Companies are also frequently using vision systems in manufacturing to identify quality issues in supplier parts, to perform in-line quality checks post-assembly.

Given that most factories and warehouses run two shifts a day, the ROI has been healthy, with paybacks typically landing within one to two years of operation.

Computer vision is a critical technology that makes autonomous vehicles possible. Advanced next-gen cars are designed to overcome driving obstacles while keeping passengers safe. Such vehicles have cameras attached to them, allowing Computer vision to create 3D maps in the realtime. Using these maps, self-driving cars can understand their surroundings better and detect obstacles in their way to opt for an alternate route.

The level of car autonomy ranges from fully autonomous to vehicles where computer-vision-based systems support a driver in different situations. Companies like Tesla, Ford, and Google are building such self-driving cars.

By recreating human ability to see, an almost endless array of Computer vision uses is rapidly coming into focus. Such a broad application is gradually reshaping industries. Various companies, big and small, find ways to leverage this innovation to reduce costs, improve the consumer experience and streamline processes. As Computer vision technology continues to prove its worth, its adoption will only increase.

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This article was written by Andrew Mikhailov. Andrew has been CTO at Zfort Group since 2017, and concentrates on growing the company into areas of modern technologies like Artificial Intelligence, BigData, and IoT. Being a CTO, Andrew doesn’t give up programming himself because it is critical for some of the projects Andrew curates as a CTO.

https://www.linkedin.com/in/andrew-mikhailov-66571912/
https://twitter.com/zfort
https://www.facebook.com/zfortgroup

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