How to download the face biometric authentication of Gansu Renshe?

Gansu face biometric authentication download operation method is as follows:

How to authenticate Gansu social security "anytime, anywhere face recognition" 1. Search for "Gansu Renshe" or scan the QR code below to download the "Gansu Renshe" APP. After the installation is successful, enter your name and ID number to log in and follow the prompts to complete the operation. 2. Search for the official account of "Gansu Provincial Department of Human Resources and Social Security" on WeChat, pay attention, enter the official account of WeChat, click on the service hall, click on biometric authentication, enter your name and ID number to log in, and follow the prompts to complete the operation.

Face recognition is a biometric identification technology based on face feature information. A series of related technologies, usually called portrait recognition and face recognition, are used to collect images or video streams containing faces, automatically detect and track faces in images, and then recognize the detected faces.

Face image acquisition: Different face images, such as static images, dynamic images, different postures and different expressions, can be acquired through the camera lens. When the user is within the shooting range of the acquisition device, the acquisition device will automatically search and shoot the user's face image.

Face detection: In practice, face detection is mainly used for preprocessing of face recognition, that is, accurately calibrating the position and size of the face in the image. Face images contain rich pattern features, such as histogram features, color features, template features, structural features and Haar features. Face detection is to pick out useful information and use these features to realize face detection.

The mainstream face detection method is based on the above characteristics and adopts Adaboost learning algorithm. Adaboost algorithm is a classification method, which combines some weak classification methods to form a new strong classification method.