The iPhone X is here, and consumers are raving about it. When released in November 2017, strong demand and long lines made the phone the most popular in years: The initial supply sold out in less than three days.
Hands down, the biggest attraction for the iPhone X is a security feature that enhances Apple’s overall mobile engagement strategy: a user-authentication application called FaceID. Instead of entering a passcode or using your thumbprint to gain access to the phone, FaceID uses a combination of technology and algorithms that recognize your face. The process works so fast, the user doesn’t even realize the complexity behind the process.
What Is FaceID?
FaceID is a form of biometric authentication, which refers to a means of using a biological characteristic to confirm identify. Science–and science fiction–have long ago introduced this concept to the public with examples like iris and thumbprint scanners.
FaceID builds an entire 3-D model of the user’s face and stores it for future reference. When a user wants to access their phone, the camera system scans the face, compares the image to the one stored, and verifies that the user is the owner of the phone.
How Does FaceID Work?
FaceID combines hardware and software platforms that work together to create a sophisticated method for authentication.
In order to use FaceID, users need to create an initial scan of their face. It’s easy–just follow the process, which basically entails taking a selfie while moving your head in a circular motion.
During this simple step, a number of things are happening, including sensors mapping the contours of your face. The flaw in previous versions of facial recognition applications was the lack of depth: someone could trick the app with a photo instead of the person. FaceID moves beyond this problem by layering three distinct measurements onto each other:
- A flood illuminator that projects infrared light on the face in any lighting environment
- A dot projector which creates a map of the dots across face
- An infrared detector that measures the effect of combining the dots and infrared light
It’s this last step that creates the unique 3-D map that is crucial to precision facial recognition. Apple estimates that the chances of the wrong person unlocking the iPhone X using FaceID are one in a million.
Once you have registered your face with FaceID, you can access your phone simply by looking at it: no thumbprint or passcode necessary. Your face acts as your passcode.
In order to determine if it’s you accessing your phone, FaceID employs neural networks to process and analyze your face. Neural networks use a sophisticated analysis of data that in this case is the mathematical representation of your face compared with the original image you set up.
Unlike machine learning, which is comprised of algorithms moving through a program in a linear fashion, neural networks work like the human brain with complex interactions between various levels of data. Machine learning makes a statistical prediction to get an answer, while neural networks make predictive decisions based on various protocols that then provide more data for more decisions. The final decision is a sum total of several previous decisions.
This predictive modeling is how FaceID can work whether you are wearing a hat or glasses, grow a beard, or physically change over time. The software compares the new image to the previous image and decides if the data matches above a certain threshold of error. For the iPhone X, which seeks to maintain security and privacy, the threshold is set relatively high.
FaceID Leverages Powerful Tools
It’s no surprise that Apple is at the forefront of tech use for the consumer market. The utility of neural networks in various industries is about to explode. As software and hardware solutions continue to evolve, prices come down and innovation goes up.
FaceID in the iPhone X is not the only use where facial recognition can provide heightened levels of privacy and security. Rumors are already flying that FaceID will find its way into HomePod (Apple’s upcoming smart speak system), iPads, and more.
As consumer demand for hands-free devices continues to grow, expect to see more and varied uses for FaceID and other facial recognition products in the future.
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About the Editor: Rae Steinbach is a graduate of Tufts University with a combined International Relations and Chinese degree. After spending time living and working abroad in China, she returned to NYC to pursue her career and continue curating quality content. Rae is passionate about travel, food, and writing, of course.