A regional feature analysis algorithm widely used in face recognition technology. It combines computer image processing technology with the principles of biostatistics, and uses computer image processing technology from video Extract the feature points of the portrait, use the principle of biostatistics to analyze and establish a mathematical model, that is, the face feature template. Use the built face feature template and the face of the subject to perform feature analysis, and give a similar value based on the analysis result. This value can be used to determine whether it is the same person.

Face capture and tracking function

Face capture refers to detecting a portrait in an image or a frame of a video stream, separating the portrait from the background, and automatically saving it. Portrait tracking refers to the use of portrait capture technology to automatically track a designated portrait when it moves within the range captured by the camera.

Face recognition comparison

Face recognition has two matching modes: verification and search. Verification is to compare the captured portrait or the designated portrait with a registered object in the database to verify whether it is the same person. Search-style comparison refers to searching for the existence of a designated portrait from all the portraits registered in the database.

Face modeling and retrieval

The registered portrait data can be modeled to extract the features of the face, and the generated face template (face feature file) can be saved in the database. When performing face search (search style), model the designated person, and then compare it with the template of all people in the database for recognition, and finally list the most similar people based on the compared similarity value List.

Live detection

The system can recognize whether the person in front of the camera is a real person or a photo. In order to prevent users from using photos, videos, masks, etc. to cheat.

Commonly used live detection is binocular camera, 3D structured light, etc.

Image quality inspection

The quality of the image directly affects the recognition effect. The image quality detection function can evaluate the image quality of the photos to be compared, and give corresponding suggestions. To assist identification.