Face recognition advantages and difficulties

Advantage

The advantage of face recognition lies in its naturalness and characteristics that are not perceived by the individual being tested.

The so-called naturalness means that the recognition method is the same as that used by humans (or even other organisms) for individual identification. For example, face recognition, human beings also distinguish and confirm the identity by observing the face, and there is also a natural recognition.

Speech recognition, body shape recognition, etc., while fingerprint recognition, iris recognition, etc. are not natural, because humans or other creatures do not distinguish individuals by such biological characteristics.

Undetected features are also important for an identification method, which makes the recognition method unobjectionable and not easily fooled because it is not easily noticeable. Face recognition has this feature. It completely uses visible light to obtain facial image information. Unlike fingerprint recognition or iris recognition, it is necessary to use electronic pressure sensors to collect fingerprints or use infrared to collect iris images. These special collection methods are easy. Being perceived, it is more likely to be deceived by pretense.

difficult

Face recognition is considered to be one of the most difficult research topics in the field of biometrics and even artificial intelligence. The difficulty of face recognition is mainly caused by the characteristics of the human face as a biometric feature.

Similarity

The difference between different individuals is small, the structure of all faces is similar, and even the structural shapes of face organs are similar. Such a feature is advantageous for positioning with a human face, but is disadvantageous for distinguishing human subjects with human faces.

Variability

The shape of the face is very unstable. People can produce many expressions through changes in the face. At different viewing angles, the visual images of the faces are also very different. In addition, face recognition is also subject to lighting conditions (such as day and night, Indoor and outdoor, etc.), many coverings of the face (such as masks, sunglasses, hair, beards, etc.), age and many other factors.

In face recognition, the first type of change should be scaled up as a criterion for distinguishing individuals, while the second type of change should be eliminated because they can represent the same individual. The first type of change is usually referred to as an inter-class difference, and the second type of change is referred to as an intra-class difference. For human faces, intra-class changes tend to be larger than inter-class changes, making it difficult to distinguish individuals with inter-class changes in the case of interference within the class.

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