Face recognition is a kind of biological recognition technology based on human face feature information. A series of related technologies, which collect the images or video streams containing faces with cameras or cameras, automatically detect and track faces in images, and then recognize the detected faces, which are also called human image recognition and face recognition.
1. Supporting night light compensation with photosensitive sensor cooperation;
2. Support serial port, Wigan 26, 34 output, output content support configuration;
3. Dynamic face detection and tracking recognition algorithm based on video stream is adopted.
4. Support devices to store 10,000 people's databases locally.
(a) Cloud platform devices support storing 50,000 face photos (less than 4,000 KB), 1 million recognition records (0.45 KB), 20,000 live snapshots
(b) LAN devices support storing 20,000 face photos (photos are calculated according to
1,000 KB) and 1 million recognition records (including the most). Nearly 10,000 live snapshots;
5. When the face database is 3000, the recognition accuracy of 1:N is 99.7%.
6. Recognition speed is fast.
(a) Face tracking and detection takes about 20 ms.
(b) Face feature extraction takes about 200 ms.
(c) Face comparison takes about 0.2 Ms. (1000 people database, average recognition takes many times). 0.5 ms. (10000 people database, average recognition takes many times.)
7. Supporting stranger detection and configurable stranger rank;
8. Supporting on-site photo preservation in face recognition or stranger detection;
9. Support HTTP interface docking;
11. Supporting the deployment of public network and local area network;
12. Supporting screen display content configuration;
13. Support Distance Recognition Configuration.
Application
Widely used in smart finance, smart city, smart campus, smart construction site, smart park, smart power, smart environmental protection, smart fire protection and smart management projects.Compatible with all kinds of turnstiles.
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