What is facial recognition?

Facial recognition is also called face recognition, face recognition, face recognition, etc. The following are all called face recognition.

A widely used regional feature analysis algorithm in face recognition technology, which integrates the computer image processing technology and the principle of biostatistics. It uses computer image processing technology to extract the image feature points from the video and analyzes the principle of biostatistics. Create a mathematical model, which is a face feature template. Using the face profile template that has been built and the face image of the person being tested for feature analysis, a similar value is given based on the results of the analysis. By this value, you can determine whether it is the same person.

Face recognition mainly has the following functions:

1, face capture and tracking function:

Face capture refers to the detection of a portrait in a frame of an image or video stream and the separation of the portrait from the background and automatic preservation. Portrait tracking refers to the use of portrait capture technology that automatically tracks a specified portrait while it is moving within the camera's range of shooting.

2, face recognition than:

Face recognition sub-verification and search-type comparison mode. Verification is to confirm whether the captured person or the specified person is compared with a registered person in the database to determine whether he is the same person. The search-style comparison refers to searching from all portraits registered in the database to find out if a specified portrait exists.

3, face modeling and retrieval:

The registered portrait data can be modeled to extract the features of the human face, and the generated face template (face signature file) can be saved in the database. When performing a face search (search formula), the specified portrait is modeled and compared with the template of all the people in the database, and finally the most similar person will be listed according to the similarity value compared. List.

4, person identification function:

The system can identify whether the person in front of the camera is a real person or a photo. In order to prevent users from using photographs to fake. This technology requires the user to make facial expressions.

5, like quality inspection:

The quality of the image directly affects the effect of the recognition. The image quality detection function can evaluate the image quality of the photos to be compared, and give corresponding recommended values ​​to assist the recognition.

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