Do Augmented Reality and Computer Vision confuse you? Here’s something even better. We’ve also got Computer vision in the mix, making things even more interesting, mind-blowing, and somewhat confusing for simpletons like us.

Here is your complete introductory guide about Augmented Reality and Computer Vision. Once we understand the terminologies and are able to differentiate one from another, we will also explore what these technologies have to offer.

What is Augmented Reality?

Think about your backyard. How would you feel if there was a pokemon sitting there? Your mobile screen can of course show you something like this, and this is what Augmented Reality really is .It augments reality with digital content. So, in a way, you see an enhanced version of reality.

Thinking you don’t really use any AR apps? . You could not be more wrong. AR apps have become so integrated in our lives, that we use them daily.
Made any Snapchat videos with the dog filter lately? Yea, that’s classic Augmented Reality for you.

Just like that, there are so many other apps that let you try different outfits and allow you to visualize how it would look instantly

The mobile App Pokemon Go that became an inescapable sensation in 2016 also was the wonder of Augmented Reality. Players had to locate and capture Pokemon characters that popped up in the real world. You may run into them on your sidewalk, in a fountain, or even in your own bathroom.

Augmented Reality has a wide range of applications. It can be used in the education sector to make the learning experience more immersive. Also, the healthcare sector can utilize technology in a variety of ways. It has opened up many new possibilities for medical image inspection or image recognition.

Virtual Reality

It is important to understand the difference between Augmented Reality and Virtual Reality (VR).

While AR adds virtual touch to existing real-world environments, VR immerses users by letting them inhabit an entirely different environment. Computers render and create this environment that is notably virtual one. Users can look up and down and feel the weather as if they were already there.

Now let’s understand the third term, Computer Vision. We will see how it is paramount for Augmented Reality in sections to come.

Computer Vision

What would you say, if someone asks you to name the objects in the picture. You will probably say a man, a woman, a table, chairs, trees, etc. If you are asked to explain the picture, you will instantly say, “A Couple having tea outside”. You will just blurt it out, without a second thought.

However, things are not that simple in the background. Human vision is an intricate piece of organic technology, which is not all about eyes and visual cortex. Moreover, it considers our mental models of objects and our abstract understandings of different things. It also utilizes our personal experiences that stem from thousands of interactions we have made with the real world, all our life.

The computer science discipline that focuses on replicating parts of the complexity of the human vision system and enabling computers to identify and process objects in images and videos in the same way that humans do, is called Computer Vision.

Given that, let’s see

Augmented Reality vs Computer Vision

What Are Computers Good At?

It is no big deal for digital equipment to capture images at resolutions and with details that outsmart the human vision system. Also, computers can detect and measure the difference between colors with high accuracy.

What Are Computers Not Good At?

When it comes to making sense of that content, computers are far behind humans. They have been struggling with this for decades. The above picture is nothing but an array of pixels for the computer.

How Does Computer Vision Enhance Augmented Reality?

It can help AR devices build a more accurate augmented environment. AR can determine where to place virtual images in accordance with space.

AR devices use GPS and compass to understand the location of a person and the direction he or she is facing, to show images against the real world background. However GPS tracking may fail when the person commutes in a congested area. Sometimes, due to this inaccuracy, AR devices place virtual images at incorrect places and build inaccurate AR environments.

Using Computer Vision techniques AR devices address the location challenges and build a more detailed augmented environment.

Computer Vision Overlapping Augmented Reality

  • Autonomous Cars – Computer vision is one of the ways self-driving cars can make sense of their surroundings. Pictures taken from different angles are fed to the software. Then it processes the images to know the real-time situation of the road. All new Tesla cars come with autopilot mode. Autopilot Augmented Vision is the new autonomous driving feature of Tesla. Their windscreens show augmented information.

    We know that Tesla is one of the few companies that have the approach of using computer vision to materialize automatic cars. Other companies are using optical waves for that. Back in June 2020, they announced that they will experiment using Augmented Reality functionalities in their cars.

  • Security Monitoring – Imagine, if your CCTV camera notifies if something unusual happens. For example, if something catches fire or a stranger lurks around the house, you get an instant alert and prevent an unfavorable situation. This is the wonder of computer vision.
    Umbo AiDome is a wonderful example of just that. They’ve come up with an autonomous security system that protects people and valuable assets alike.

  • Image & Face Recognition – The role of computer vision in facial recognition apps is essential. This technology allows computers to match the images of people’s faces to their identities. The algorithms detect facial features in images and compare them with its database of face profiles.
    A brilliant example of this would be Uplara. It’s a virtual try-on for e-shoppers. The amazing thing about this one is that you can integrate it on your Shopify store, and give people an AR-powered eCommerce experience.

  • Health and Diagnostics – Such applications also have the potential to play a role in medical science, since a lot of image recognition is required there. Tasks like detecting cancerous moles in skin images and finding symptoms in x-ray and MRI scans can be automated.
    Imagine preparing for surgery on your mobile. Sounds bizarre, right?
    Well, think again because mobile applications like Touch Surgery allow anyone in the world to learn and prepare for surgery based on industry-approved best practices and that’s just one example.

  • Vision Based Biometric Authentication – Here is one of the greatest applications of computer vision and AI-powered facial recognition. Employees login virtually on the remote workspace. The unique biological retina of the user is used to verify the identity.

    Computer Vision and Artificial Intelligence empower the Face Reg application, which is an easy-to-use and scalable facial recognition app. It compares the features of faces or objects detected with images that come from a predefined dynamic dataset to provide maximum accuracy possible. It can also be used for video surveillance.

  • QR Codes Scanning – Computer Vision can scan QR codes and collect the information stored in them. AR can further display that gathered information to users. It is useful for both businesses and customers.
    For example, let’s consider some packed fruit products. A food company can store all details like ingredients and how food is packed into QR codes and paste the code on the packet. When a product reaches the consumer’s hands, they can use AR devices with computer vision to scan the code and read information.

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Putting It All Together

The technologies that can easily gather user data (Big Data, IoT) has made it easier to train computer vision programs. A wide range of applications and intelligent products can now be materialized with the help of technology. Augmented Reality, on the other side, has even made its way into content marketing and digital marketing strategies. Mainstream adoption of both technologies as well as their merge is exponentially increasing.

As more and more enterprises adopt the method of using computer visions to help AR projects build real environments, the competition will get tougher and tougher.

Would you like to jump in today or when the hard times come?