With the rapid development of face recognition technology in the past two years, the increasing recognition accuracy and recognition speed provide a technical basis for the application of face recognition in many fields. Since 2015, the application field of face recognition has increased significantly, until 2016. In the second half of the year, the application speed of face recognition technology has obviously accelerated. After entering 2018, the popularity of face recognition has ushered in a blowout, and he has been in many fields.
What is Face recognition technology?
Like other biometric identification security technologies such as a fingerprint (uses finger) and voice recognition (uses vocals/sound); the Face recognition is another very common technology now, which can easily see in your smartphones, nowadays, that uses human’s face to unlock the devices.
So, the definition of face recognition will be- a biometric identification technology that uses sensors to recognize human or any other face to secure some particular product or environment.
The products of face recognition are also increasing. According to the function, they are mainly divided into the following types: Security typeface recognition products, Enhanced management typeface recognition products, and Entertainment typeface recognition products.
The application fields also include the following categories: military, public security, justice, finance, social insurance, enterprises and institutions, factories, schools and other industries, and the scope of application is also very wide, such as warehouses, computer rooms, office buildings, offices, data rooms, Archives, laboratories, etc. access control, attendance check-in, patrol, identification, early warning and other applications.
What are the advantages and disadvantages of face recognition technology?
1. Natural recognition: It refers the natural process of identifying as we do, that means the technology that is enough smart and capable to naturally distinguishing and confirming identity by observing and comparing faces; the speech recognition and body shape recognition are also falling under this category. But not intact like fingerprint recognition and iris recognition those cannot be passed/spoof by humans or other creatures easily.
2. The recognized face image information can be actively acquired without being perceived by the measured individual. Face recognition has to obtain facial image information by using visible light, and different from fingerprint recognition needs to be collected by the electronic pressure sensor. Fingerprints, these special collection methods are easily detected, and can be deceived by camouflage.
3. Compared to other biometric technologies, face recognition is non-contact, users do not need to be in direct contact with the device.
4. Concurrency, in the actual application scenario, face recognition technology can sort, judge and identify multiple faces.
5. The first is the similarity of human faces. The differences between different individuals are small, the structures of all faces are 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. The cover of the makeup and the natural similarity of the twins add to the difficulty of recognition.
6. There is volatility in the face, the shape of the face is very unstable, people can produce a lot of expressions through the change of the face, and the visual images of the faces are also very different at different viewing angles. In addition, the face recognition is also affected by Light conditions (such as day and night, indoor and outdoor, etc.), many coverings of the face (such as masks, sunglasses, hair, beards, etc.), age and other factors.
7. At the same time, with the increase of the number of people to be identified and the increase in the probability of people who are more like, the original face recognition can not meet the practical application. The existing deep learning technology has greatly improved in these aspects. At present, many manufacturers’ face recognition technology has achieved more than 99.5% in LFW evaluation, and some close to or even exceed the recognition rate of the human eye. This provides technical support for the large-scale practical application of the face recognition system. With the continuous advancement of technology, it is expected that one day these problems in the face recognition field will be solved perfectly.
Nowadays, a new generation of technological revolution represented by face recognition has emerged. This will be an era of technological competition. Technology research and development will become an important factor in enterprise development, and business models will change with technological innovation.