Technical Features
Face Recognition Technology Center Page
Auto adjust dynamic exposure and analyze the
key points of face
Suitable for Various Environments
Face Image Location
32, 128, 256 Positioning Points
Support Facial Features with Different Accuracy
Accurately Recognize Multiple Facial Features
Age, Gender and Hair
Analyze the 3D Contour of Human Face
Refuse to Recognize Fake Faces
Intelligent Detection
Support the Detection of Safety Helmet
About Face Recognition
Face recognition products use image processors. It can detect the brightness of the face, automatically adjust the dynamic exposure, track and detect the face, analyze the key points of face, and auto adjust the image magnification, recognition and comparison.
FCARD face recognition technology adopts in-depth learning algorithm, scientifically self-learning and improving algorithm library to improve recognition accuracy, face tracking and detection ability. It obtains the face features through analyze the key points of face, combined with face attributes and other operations to achieve accurate face comparison.
Face Detection
Our face recognition technology can detecting of various actual environments such as face, side face, semi occlusion, blur, dark light, backlight, expression change and face angle. It supports video recognition or photo recognition of color, gray, near and far infrared lights.
Facial Feature Point
From the in-depth detailed analysis of the eyes, mouth, nose, contour in the face and so on, it can identify 32, 128 and 256 key points. Under the deeply optimized Linux system, it supports the recognition of facial feature points with different accuracy, which can be completed as soon as milliseconds. After optimization, it also can be applied on various scene such as large angle side face, large expression change, partial occlusion, blur, light and shade change, etc.
Facial Attributes
Our face recognition technology can accurately recognize a variety of face attribute types, such as gender, age, clan, skin color, expression, beard, etc. According to various attribute differentiation, face categories are classified and excluded, so that to speed up the calculation efficiency of face recognition.
Liveness Detection
We use infrared cameras to detecting infrared inspection on living people, analyze the three-dimensional contour of human faces, and check the three-dimensional changes of human face movements, so that to prevent high-definition photos, screen portraits, portrait masks and other fake fraudulent faces. Realize true and false face recognition.
Eyes and Wears
In real scenes, we maybe wear glasses, hats and others. In our face algorithm, it can intelligently detect hats, eyes and facial occlusion, support the recognition of whether to wear hats and other technologies.
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