Facial Recognition – An Overview

Face recognition is a computer technology that recognizes human faces in digital images and is used in several applications. The psychological mechanism by which humans identify and attend to faces in a visual scene is known as face detection. To begin, all the areas in the gray-level image are verified for potential human eye areas. The genetic algorithm is then used to construct all of the possible face regions, such as the brows, iris, nostrils, and mouth edges, using the genetic algorithm.

How does it work?

Biometrics is used in a facial recognition system to map facial features from an image or video. It compares the specifics to a database of recognizable faces to find a match. This is due to the fact that facial recognition has many commercial applications. It can be used for a variety of purposes, including surveillance and marketing.

Key Capabilities of this technology:

  • Recognize and identify facial features – Get the coordinates of any face detected eyes, ears, cheeks, nose, and mouth.
  • Get the outlines of detected faces’ eyes, eyebrows, lips, and nose – Get the contours of detected faces’ eyes, eyebrows, lips, and nose.
  • Facial expressions recognition – Determine if a person is smiling or has their eyes closed by recognizing facial expressions.
  • Face tracking through several video frames – Get a unique identifier for each person whose face is identified. 
  • Real-time recognition – Face recognition is done on the device and is quick enough to be used in real-time applications like video manipulation.

Who Makes Money From Facial Recognition?

MorphoTrust, a division of Idemia (formerly OT-Morpho or Safran), is one of the leading suppliers of facial recognition and other biometric security technology in the U. S. State DMVs, federal and state law enforcement, border control and airports, and the state department have all used its systems. 3M, Cognitec, DataWorks Plus, Dynamic Imaging Systems, FaceFirst, and NEC Global are some of the other common vendors.

Algorithms preferred for Facial recognition: 

Based on the most commonly used criterion, five different algorithms have been chosen. Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), skin color, wavelet, and Artificial Neural Network (ANN) are used.

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