How Augmented Reality Works
First off, let’s elaborate on what we mean by Augmented Reality (AR). In essence, AR is when you are presented with a real-life image/visual that is also accompanied by topical, relevant, background information that makes the image all the more useful. One example could be watching a motorcycle race and having a slow-motion replay of a rider and his motorcycle which also shows information like the lean angle, gear position during entry into the corner, g-force figures etc.
Another way of looking at it is by considering AR as being a blend of real life and virtual reality where the extra information provided to you is highly topical and relevant to what you want to know at a certain place and time.
In today’s context, the ideal use of AR would be for the provision of practical information, e.g. where’s the nearest coffee house/bakery, the nearest cinema/petrol station/ATM machine etc. Thanks to the miniaturisation of mobile devices, we can already find all that information in the palm of our hands via our mobile devices.
How does AR know where you are?
Before you can even access the information provided by AR, an AR application needs to know where exactly you are in the world. This is known as tracking and the most rudimentary form of tracking is via the use of GPS (or some other satellite navigation system) to determine your position. Alternatively, Wi-Fi hotspots can also assist in keeping track of your location. Once the AR app knows where you are, it can start relaying the relevant information automatically.
It’s all in the details
Moving in closer, GPS is unable to provide information for certain objects at a specific location, due to the ever-changing nature of the information. For example, in an art gallery, a certain painting could have additional information on it, which could only be accessed with an AR app. This is where Markerless Tracking and Marker-based Tracking come into the picture.
All you need to do is point your smartphone at a picture or exhibit and have some kind of pattern recognition or feature-detection system try to identify it. This is actually quite similar to how our own perceptual systems work. That’s a fancy way of saying what our eyes see. Once we see an item, our brain will try to summon additional information from our memory. Depending on whether we’ve previously digested information related to what we’re currently seeing, we’d be able to know certain details, or perhaps nothing at all about the picture/exhibit.
A much simpler and smarter option is where the gallery or museum prints small, two-dimensional barcodes (a.k.a. data-matrix codes) next to each item on display. All that’s left to do is to point your phone’s camera at one of them, whereby your phone would then re-interpret the barcode as a web address, and its built-in browser would open the relevant web page containing further information. The beauty of this concept is where AR apps can be created to read all kinds of other markers (or fiducial markers) as these “added reference points” are called.
It goes without saying that the relative ease of implementation for marker-based tracking automatically makes it a much more popular option. However, in keeping our technology human-based, we find that markerless tracking is actually closer to what we would be comfortable with – as it would function almost like our own visual systems do. For example, we recognise our friends by their face, not by some barcode printed on them.
Where do we go from here?
We’re far from a mature virtual reality (VR) and augmented reality (AR) market, but the buzz is certainly growing in these early stages. Between July 2015 and July 2016, VR and AR startups received over $2 billion in VC funding – and the growth is only expected to continue.
While there are plenty of potential use cases for VR and AR technology, the reality is that virtual/augmented reality applications require more maturity at the hardware level to truly take off.
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