What Is Image Recognition Technology?
Image recognition goes far beyond Facebook automatically finding your contacts and suggesting tags in posted photos. That’s an example application, of course, but we’re talking about a whole different ball game when it comes to search. Image recognition technology identifies and organizes the various components of images, from faces to logos to objects.
Rapidly analyzing and classifying high volumes of images for search purposes requires the same sort of deep-learning algorithms used in voice recognition and self-driving vehicles. The thing to remember about these AI technologies is that they get smarter and faster as they go. The more photos they “read,” the more accurate they’re going to get. With the number of images shared each day ranging from 1.8 to 2 billion depending on whom you ask, there’s no shortage of images to examine. (On a side note, this most certainly means Big Data is about to get a whole lot bigger—but that’s a story for another day.)
Google has already implemented image recognition software (no surprise there) into its consumer-facing Google Photos. The platform takes a look at the photo collections of each user and sets out to organize them by categories. That’s novel in and of itself, but it gets better: Consider that these categories used to only be classifiable by tags submitted by users themselves—things like person, activity, subject, or place. Now, that’s done using AI.
Image recognition technology doesn’t only save consumers time—there are also huge monetization prospects for brands. Mobile-first apps and social platforms are helping spur that growth.
Mobile-First, Visual-First Apps Leading the Charge
It’s no secret that mobile has changed how we live and work, but taking a look at the numbers still provides some serious perspective at just how great that change is. For example, Pew reports that almost two-thirds of Americans own smartphones, and Deloitte says we collectively check them eight billion times per day—that breaks down to an average of 46 times per day for individuals. Many apps are made for mobile, and many mobile apps are visual-first: It just might be the perfect storm for image recognition technology.
Two examples of visual-first apps are Instagram and Snapchat. (By the way, Snapchat users share 8,796 photos per second—a staggering number that is only growing.) Facebook and Twitter, too, are growing significantly more visual—but let’s take a moment and focus on another platform that’s made pictures its bread and butter: Pin anything lately? Pinterest allows members to zero their cursors over a particular object in a photo, like a piece of furniture, and image recognition automatically gathers other like images. There are significant marketing implications here, as brands can use the content of images to help target where ads are positioned while improving overall execution.
What’s Next?
Image recognition technology is primed to be a game changer for search (and advertising) as we know it. Think of it as the Google AdWords of pictures with the mega implications and clear concept of Boolean search. With mobile-first, visual-first apps leading the charge and AI technologies surging from a simmer to a boil, it’s not like this development is going anywhere anytime soon.
How do you feel about image recognition technology and search? Do you see any possibilities here for your business when it comes to advertising? Just think—as the algorithms become smarter in time, the insight you’ll receive will become even more useful. I know I’m intrigued by the possibilities. Are you? Let’s hear it.
Other Resources on This Topic:
Deep Learning’s Impact on SEO
How Will Google “Read” and Rank Your Images in the Near Future
Shopping Ads Now Included in Google Image Search on Mobile