This technique is very challenging, and will be even more so in the future, even though we encountered systems with terribly low efficiency. Examples worth mentioning as deterrents, are systems with above 70% false rejection rate. Nowadays facial recognition systems are developing in two main directions.

2D Facial recognition

Essentially there are two solutions AT present: sample based: this examines the portrait itself and compares the portions of the face geometry based: this identifies and analyses the features of the face (nose, mouth, eye, chin) and compares their positions

The high user acceptance of facial recognition is easily understandable, but we have to be realistic with our expectations with this kind of technology.

3D Facial recognition

This method analyses a 3D picture that is produced by multiple cameras.

Contrary to the 2D systems, this technique is more reliable. It’s less sensitive to the rotation of the head or change of lighting. By using infrared light, the geometry of the face is identifiable even in the dark.

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