Face recognition technology does not include face beautification.
Some aspects of face recognition technology include:
1. Face Detection: The first step in face recognition is to detect the location of the face in the image. Face detection technology can automatically identify the face region in the image, providing the basis for subsequent feature extraction and matching.
2. Face feature extraction: extract a set of feature vectors in the face image, these feature vectors can represent the unique features of the face, such as the location and shape of the eyes, nose, mouth, etc.. Commonly used feature extraction methods include Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), and so on.
3. Feature Matching and Comparison: Match the extracted face features with the known face features in the database to determine whether the match is successful to recognize the identity. The matching process may involve techniques such as similarity calculation, pattern matching, and so on.
4. 3D Face Recognition: In addition to face recognition based on 2D images, there are also technologies based on 3D face models. These techniques can improve accuracy and security by obtaining depth information about the face.
5. Live-body detection: To prevent spoofing using inauthentic samples such as photographs, face recognition systems often require live-body detection to determine that the person being detected is real.
6. Large-scale face recognition: Large-scale face recognition systems can cope with the recognition needs of larger pools of people, such as face access control systems, surveillance systems in public **** places.
7. Mobile Face Recognition: With the popularization of smartphones and mobile devices, mobile face recognition technology has been widely used for unlocking cell phones, payments and other functions.
8. Face Recognition in Social Security: Face recognition technology is widely used in social security, such as in the monitoring system of public **** places, used to find missing children, tracking suspects and so on.
9. Face recognition in the commercial field: Face recognition technology in the commercial field can be used for traffic statistics, advertising push, user analysis, etc., to help enterprises better understand and serve customers.
10. Face recognition in the medical field: Face recognition technology in the medical field can be used for the identification of doctors and patients, to improve the security of medical information.
11. Face recognition in the field of education: face recognition technology can be used for students' attendance, teachers' work check-in, etc., to improve the efficiency of education management.
12. The development trend of face recognition technology: With the development of artificial intelligence and deep learning technology, face recognition technology is moving towards higher accuracy, faster processing speed and a wider range of applications. At the same time, face recognition technology is facing some challenges and discussions in terms of privacy protection and ethics.