Consumer’s demand for face recognition technology, popularized in the iPhone X, is also being met in surprising places– like burger joints.
Industries besides consumer electronics had the opportunity to implement it as the technology developed, but relatively few companies took advantage. Most notably is the iPhone X, which drew buzz over its face recognition feature.
“While the introduction of Face ID naturally raised a number of pertinent questions about usability, it turns out that Face ID works as well as advertised,” according to BGR. “Indeed, many users actually find Face ID to be as seamless as Touch ID, if not more so.”
Consumers approved of and appreciated the technology as a feature of the product in this context.
“Its camera is the major driver among positive ratings and in particular, the front facing camera which allows Apple’s new security feature, Face ID, is a key market differentiator,” Strategy Analytics reported, based on early adopter reviews from online retailers.
Face ID for Food
If the technology was so popular among consumers, why not implement it into categories such as food service?
CaliBurger, a California burger company, “has made waves with its focus on using robots for jobs typically reserved for humans,” according to Business Insider. “The chain uses a robot to flip burgers in the kitchen and is developing infrastructure to replace food deliverers with autonomous vehicles.” They plan to begin the implementation of face recognition technology in 2018.
With the NEC Corporation of America, Cali Group introduced AI-enabled kiosks that use face ID to create a more convenient transaction for consumers. Cali Group reported Dec. 19:
“Customers will have the option of immediately activating their loyalty accounts as they approach the kiosks without needing to swipe a card or type in identifying information. The loyalty account shows a customer’s favorite historical meal packages, enabling the customer to complete the ordering transaction in a matter of seconds.”
The pilot program is only at CaliBurger’s Pasadena location– a showcase for new technology from the parent company. Pending the success of the kiosks, they will spread across to other stores in 2018.
“Also in 2018, the platform will be used to allow customers to pay using their faces,” Cali Group reported.
NEC’s NeoFace face ID software offers a competitive edge to CaliBurger’s service, much like the iPhone. It provides a customized, interactive experience with the customer and is currently somewhat of a novelty. John Miller, Chairman and CEO of Cali Group, said in the report:
“Face-based loyalty significantly reduces the friction associated with loyalty program registration and use. Our goal for 2018 is to replace credit card swipes with face-based payments. Facial recognition is part of our broader strategy to enable the restaurant and retail industries to provide the same kinds of benefits and conveniences in the built world that customers experience with retailers like Amazon in the digital world.”
Face ID for Social Media
Speaking of the digital world, Facebook is in on the trend with major improvement in face-processing software.
When identifying whether two unfamiliar pictures show the same person, people answer correctly 97.53 percent of the time compared to the 97.25 percent scored by Facebook’s software, according to MIT Technology Review.
radio: facebook's new feature will notify you whenever a photo is posted with your face in it, even if you aren't tagged, using facial recognition
mom: ugh, thats gonna be so annoying. people are sharing photos of jennifer aniston all the time i'm gonna get so many notifications
— lauryn ⛵️ (@laurynshiplett) December 21, 2017
Facebook is largely successful because of its access to data.
Neeraj Kumar, a researcher at the University of Washington, said “I’d bet that a lot of the gain here comes from what deep learning generally provides: being able to leverage huge amounts of outside data in a much higher-capacity learning model,” reported MIT Technology Review.
Facebook can feed data from a slice of their collection of user images, “four million photos of faces belonging to almost 4,000 people,” to train their network.
It’s all about meeting the demand for face recognition technology, and companies outside the consumer electronics industry invested.