Thai
Elite Member
You're an idiot. STFU. Thanks dude.
Moving on (again), how FaceID works: https://www.forbes.com/sites/jvchamary/2017/09/16/how-face-id-works-apple-iphone-x/#24d0c3d6624d
From article:
"Here are the steps for image capture:
1. The proximity sensor and ambient light sensor help the TrueDepth camera system determine how much illumination will be needed for face recognition;
2. The flood illuminator produces infrared (IR) light, part of the electromagnetic spectrum that's invisible to the naked eye, to illuminate your face;
3. The dot projector produces more than 30,000 dots of invisible IR light to create a three-dimensional map (for area and depth) of your facial landscape;
4. The infrared camera captures images of the dot pattern and the IR light (a heat signature) that's been reflected back from your face.
When a biometric system is set up, a computer -- such as the processor in your smartphone -- will capture and store the reference patterns, known as a template or 'enrolment image'. Then when you want to access a device (e.g. unlock your phone), you present the computer with a 'verification image'.
"Internally it computes a score between 0 and 1," says Jain. "If it's closer to 1, that means it's the same fingerprint or face. If it's closer to 0, it's not the same person."
As the enrolment and verification images won't be identical due to differences in capture conditions, your phone uses a threshold to determine whether they're significantly different. A comparison score of 0.7 might be close enough under some scenarios, for example, and that minimum score is not a fixed number.
All the calculations happen too fast for you to notice, thanks to the power of smartphone processors. iPhone X uses a 'Neural Engine' that, as Apple marketing chief Phil Schiller boasted, "can perform over 600 billion operations per second, and it's used to do real-time processing of Face ID recognition."
Here are the steps for face recognition:
1. The IR images are sent from the camera to iPhone X's 'Neural Engine' computer processor to build a 3D mathematical model (map) of your face;
2. The 3D model or 'verification image' is presented to the computer's algorithms and compared against your stored template or 'enrolment image';
3. The processor calculates whether the verification and enrolment images match, based on a comparison score of similarity between your images;
4. The phone authenticates your identity and unlocks (or authorises a payment) if the comparison score is higher than a certain threshold value.
Better face recognition occurs thanks to so-called 'neural' technology. Schiller said that iPhone X's Neural Engine is "specialised hardware built for a specific set of machine learning algorithms" and Apple "developed multiple neural networks to create Face ID." What does all that technobabble really mean?
Machine learning algorithms are the instructions that allow machines to adapt, while an artificial neural network is a computer system inspired by the brain, whose interconnected structures (particularly neurons) provide the incredible processing power that enables an animal to learn and adapt to its surroundings.
Precisely how Apple's machine learning and neural network actually work isn't important, only that it lets Face ID continually update its algorithm so that it's able to recognize you when your appearance changes."
