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The new Face ID technology: is it a revolutionary invention?

August 30, 2019

What is Face ID 

Face ID is enabled by the True Depth camera and is simple to set up. It projects and analyzes more than 30,000 invisible dots to create a precise depth map of your face. Face ID works with iPhone X and unlocks only when you’re looking at it. It’s designed to resist spoofing by photos or masks. Your facial map is encrypted and protected by the Secure Enclave. And authentication happens instantly on the device, not in the cloud.

Face ID uses the A11 Bionic chip for the machine learning to recognize changes in your appearance. You can put on glasses, wear a hat, grow a beard. Even wild makeup will not fool Face ID, it will know you. Your friends might not recognize you, but iPhone X will.

Advantages of Face ID

      1.Greater Accuracy: 3D mapping, deep learning and other advances make FRT more reliable and
      harder to trick.
  1. Better Security: Research shows a 1-in-50,000 chance of a phone with touch ID being unlocked with the wrong fingerprint. With 3D facial modeling, the probability drops to nearly 1-in-1,000,000.
  2. Convenient and Friction less: FRT is easy. It can be used passively without a user’s knowledge; or actively, such as having a person “smile for the camera.”
  3. Smarter Integration: Face recognition tools are generally easy to integrate with existing security infrastructures, saving time and cost on software redevelopment.
  4. Automation: Automated and accurate 24/7 security eliminates the need for security guards to visually monitor entry points, perform security checks and view security cameras. 

        Disadvantage of Face ID Technology

       1. Processing & Storing

  1. Storage are like gold in a digital world since you have to save huge amounts of data for future usage. Even though you get HD-video in a pretty low resolution, it still requires a significant space. Just as the high-quality image visuals. There is no need to process every video’s frame – it’s an enormous waste of resources. That’s why most of the time only a fraction (around 10 – 25%) is actually being put through an FRT.
    Professional agencies use whole clusters of computers in order to minimize total processing time. But every added computer means considerable data transfer via network, which can be influenced by input-output limitations that lower a processing speed.

    2 . Image Size & Quality

    It’s obvious that a facial recognition is a super advanced software that requires HQ digital cameras for algorithms to operate accurately. A face-detection system captures a face in the photo or screen-shot from a video, then the relative size of that face image will be compared with the size of enrolled one. So, the photo’s quality here affects the whole face recognition process, how well it would be done. Imagine, the already small size picture is coupled with a distance that was between a target and a CCTV… What proportions will the detected face have? No more than 100×200 pixels.
    Pretty hard to get a clear identity in such case. What’s more, scanning a photo for varying face sizes is a processor-intensive task. Most systems allow identification of a face-size range to eliminate false recognition and speed up image processing. But the initial investment in such face tracking software is not a cheap one, however, it will pay off in no time.

    #3. Surveillance Angle

    The identification process is also under a great pressure of the surveillance angle that was responsible for the target’s face capturing. To enroll a face through the recognition software, the multiple angles are being used – profile, frontal, 45-degree, etc. But to generate a clear template for the face, you’ll need nothing less than a frontal view. The higher resolution photo has and the more direct its angle is (goes for both enrolled and compared images) the more accurate resulting matches would be.

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