You probably use Computer vision every day and don’t even think about it. Enjoy checking out the latest Snapchat filters? That’s computer vision. Unlock your iPhone with your face? That’s computer vision, too. Use your phone to deposit your latest paycheck and get some cash in your bank account? Well, that’s also computer vision.
Computer vision as we know it is at a tipping point. Thanks to industry-wide development efforts and advances in deep learning algorithms and graphics processors; we’re doing things that were unimaginable just a decade ago.
Some of the technology has been around for a few years, but a handful of developments in the past year have taken computer vision to new heights. The confluence of better sensors, a massive number of labeled images, easy access to deep learning software, and improved processors have combined to create functionality that was available only to a limited handful of large tech companies just a year ago.
It would seem the future is imminent.
The ambitious computer vision projects we have seen in 2018 signify that the technology is finally catching up with the applications that developers have long yearned to create. It also means that it will soon get cheaper to develop tailored computer vision applications.
ModiFace, for instance, lets users try on makeup using only their smartphones. Topology does the same for eyewear. MTailor makes custom-tailored jeans and shirts using a similar process. Outside of fashion, Pottery Barn lets users see what new furniture might look like in their homes, and Hover turns users’ pictures of their homes into fully measured 3D models.
None of these projects is as complicated as self-driving cars and cashierless grocery stores, but that’s what qualifies the current generation of computer vision products as a harbinger for massive deployment in the next few years: Once it becomes possible for small companies to develop functioning computer vision products for a mass audience, the technology will begin infiltrating almost every part of our lives.