Each time you recognize someone’s face, you’re using an internal form of facial recognition. In a matter of milliseconds, your mind breaks down the parts of their face, puts them back together, and matches the sum with those faces already stored in your memory. When the process works seamlessly, you don’t even realize that it’s happening.
While you may not have given much thought to how your brain distinguishes one face from another, the behind-the-scenes process is fascinating and serves as the foundation for modern facial recognition apps. Though still considered an emerging technology, facial recognition is already being used in a number of applications ranging from social media to security. As more businesses consider applying this technology to their own organizations, it’s essential that they consider both the benefits and potential pitfalls of doing so.
How Does a Facial Recognition App Work?
We’ve covered this topic in detail in a previous blog post. Let’s briefly outline the basics necessary to understand the rest of this article.
Classified as a form of biometric identification, because it extracts information from the human body, much like retina scans and voice recognition, facial recognition software is designed to figure out what makes one face different from another. It does this by completing three key steps: face detection, faceprint creation, and identification. During this first step, the software picks out faces, as defined by the deep learning model it is based on. In short, the system is making sure that a face is a face and not, say, a ball or a pizza.
Once the system detects a face, it then begins making sense of it by creating a faceprint. Just as each person has a unique fingerprint, they also have a unique face. The distance between someone’s eyes, the length of their nose, and the shape of their mouth are just a few of the metrics that a facial recognition system uses to create a unique faceprint. While most systems can’t consistently differentiate between identical twins, some, like the iPhone X’s Face ID, are sophisticated enough to do so with a high degree of certainty. The result of all of these calculations is a mathematical formula that separates one face from another.
Factors Affecting the Quality of Facial Recognition
The size, shape, and angle of a photo affect the ability of a facial recognition app to correctly identify faces in it. The image obtained in the initial stages may need to be resized or reoriented in order to improve the system’s recognition capabilities. Hi-resolution 2D and 3D images typically produce the best face matching results. However, one of the most significant factors influencing the quality of facial recognition is lighting. A photo with a well-lit front-facing face and unobstructed view is considered ideal. How far away a face is from the camera, the expression that the person is making in the photo, and the degree of contrast between the face and the background all have a similar impact on the efficacy of facial recognition systems.