Working in harmony: Augmented Reality and Machine Learning
Augmented Reality (AR) and Machine Learning (ML) are two big players in the technological world right now. Both of them are advancing at a rapid pace in an attempt to fuel the tech needs in their respective fields.
But, as they continue to develop, we’re beginning to see the two come together to form a new dynamic duo, with many looking at how ML can be used to enhance AR.
In our quest for immersive and dynamic content, it’s perhaps not so unexpected that these two technologies have combined to become an unstoppable force—especially with the demand for more personalized content for consumers.
By integrating machine learning and augmented reality, it expands the range of what we can do with AR experiences and can add the more personal touch users are yearning for.
So, just how are AR and ML being used together?
Content tailored to you
Immersive content is a key part of AR’s appeal to consumers. So it’s no surprise that one of the first, and more obvious, areas we’re seeing development is content on mobile apps.
There are some instances where ML and artificial intelligence (AI) are already beginning to play an essential role in AR apps, but it’s far from the standard.
The possibilities ML presents for these apps are endless. With the ability to track and understand the 3D world, machine learning adds extra detail to augmented reality and can be used to build more immersive experiences that are tailored to the individual.
When people use AR on their phones, the apps almost always require the camera to be open. This could be used to collect image data using ML, or track objects and display information.
Neural networks and deep learning techniques can also then learn from this data it collects, and not only add more interactivity to AR scenes but further enrich the users’ experience. A good example of where this is already being used is Google Lens—Google’s translation app. It enables users to scan foreign signs and will translate them instantaneously.
IKEA Place is another example, allowing users to buy furniture without leaving their homes. The ability to see how a sofa would look in your living room is quite a straightforward idea but a somewhat revolutionary use of AR, and if ML was thrown into the mix, it would enhance the experience even further.
Not only could it remember previous items you’ve brought, but suggest products based of the style of furniture you’ve gone for before or match items with furniture and decor you already have in your home—who knew furniture would be at the center of technological advancement?
It’s clear that, in the next few years, we’ll begin to see an increase in these immersive AR apps thanks to the enhancements machine learning brings, with users can discovering more engaging and unique experiences.
It’s right in front of your eyes
Another area benefitting from the integration of ML in augmented reality is smart glasses. Whenever AR is discussed, the conversation always leads back to AR glasses, and while they weren’t necessarily a stand-out success, introducing machine learning may be a way to bring AR glasses back into the limelight.
There’s a lot to be said about this particular pairing, mainly because out of everything, this can give users the most personalized experience.
To start with, users are wearing the tech, and ML learning can be used to collect data from what the person is seeing or doing. It can then overlay information taken from any image or speech recognition data collected from the glasses, and place this on the lens of the user.
Varia Vision has done just that. Their smart glasses use a combination of ML and AR to detect traffic, performance, route directions, and more and then display this on the lens of the user, without blocking their vision.
This concept is also being seen in AR training simulators, specifically in the military, and while these don’t necessarily involve the user wearing smart glasses, the same principles are applied. It allows for a soldiers’ progress to be tracked whilst in the simulation, and can also give the best course when on operations.
Machine learning brings a new level of immersion to AR glasses, as it can monitor the preferences of a user and build a more intuitive smart glass interface. It might even go so far as to make the user forget they’re wearing the glasses at all.
The possibilities are exciting and varied, and although we’ve seen many different types of AR glasses hit the market, the integration of machine learning might just be what they need to meet the demands of the masses.
Dressing up in AR
Augmented reality and machine learning are also shaping the way we, as consumers, shop. All of those who saw 1995’s Clueless, and sat in awe as Cher virtually tried on outfits before deciding what to wear, well, the time has come for this to be our reality—finally!
Take L’Oreal, which acquired its own tech company, ModiFace, in 2018 and has been leading on the AR front. From its ‘Magic Mirrors’ to the Make-up Genius app, which lets users try on different make-up and hairstyles virtually, the brand is proving to be a pioneer in branded AR experiences, but what if machine learning was integrated into these?
To start, it could use the data to record the products a shopper is interested in, suggest similar items, and remember certain products they’ve brought before. What’s more, the ‘Magic Mirrors’, or smart mirrors as they’re more commonly known, aren’t just being utilized by L’Oreal.
These use cases aim to improve user experience, and integrating machine learning algorithms would make them even interactive and unique. Plus, by using these AR apps and devices, consumers are helping to strengthen brands and their product offerings.
A step on from this is how AR is being incorporated into the design aspect of products, as you can see with Foundry’s research project Colorway AR, in collaboration with The Footsoldiers. Many companies have been using AR to enhance their creative production process, offering a new way for designers to view objects in AR before physical sampling. This saves a huge amount of time and resources and speeds up the review process.
All in all, this new interactive way of retail is set to change the way in which consumers shop and how brands shape their shops/experiences, and their design processes.
The future of ML and AR
It’s not just mobile apps and retail that AR and ML are making an impact. There has been research happening on how it can be used in surgery and healthcare. We’ve spoken about how virtual reality (VR) is making waves in medicine before, but ML and AR could enhance these even further, and continue to make a real difference.
Plus, AR and VR add a new level of immersion to training environments, and adding machine learning allows for more in-depth training—not just in medicine, but education, the military, and more. It can personalize and adapt training to optimize performance.
With all this being said, it’s clear that augmented reality has come a long way since it first appeared in the tech market.
From phone apps like Snapchat to real-world use cases, machine learning could make richer experiences for those using AR and make a profound impact on the way we use technology.
