What is the principle of face recognition technology now?

The principle of face recognition technology mainly depends on image processing and machine learning methods. Firstly, the technology detects the face of the input image or video frame to determine the position and size of the face. Then, through a series of feature extraction algorithms, key features are extracted from the face image, such as the shape, size and position relationship of the face contour, eyes, nose and mouth. These features are converted into digital vectors for subsequent matching and recognition.

Machine learning algorithm plays a key role in face recognition. By learning a large number of face images, the algorithm establishes a mathematical model of face features, continuously optimizes model parameters, and improves the accuracy of recognition. In practical application, the system will compare the extracted facial features with the facial features in the database to find the most similar result or results, so as to realize identity authentication or identification.

In addition, with the development of deep learning technology, face recognition technology has been further improved. By constructing the deep neural network model, the deep learning algorithm can automatically learn and extract more complex and abstract facial features, thus improving the accuracy and robustness of recognition.

It should be noted that face recognition technology still faces some challenges in practical application, such as lighting conditions, facial expressions, posture changes and other factors may affect the recognition effect. Therefore, researchers need to constantly explore new algorithms and technologies to improve the performance and stability of face recognition technology.