The network camera can identify human faces by itself based on recognizing personal facial features. Edge computing can reduce network throughput and enhance back-end performance.
The network camera can identify human faces by itself based on recognizing personal facial features. Edge computing can reduce network throughput and enhance back-end performance. Hunt camera is embedded with AI chip and proved to be 99% accurate and robust in variant situations.
• Face Detection / Tracking / Recognition
• Gender and Age Estimation
• White/backlist and action trigger in 0.8 seconds
• Region filter and crowd filter
• Max. 30 degree of rotation
• Wide dynamic range to work in back light and low luminance condition
• Max. 10000 faces to enrol from live, snapshot, and batch images
• SDK for integration
Access Control of Intelligent Building
Entrance control with access card or password input usually cause queuing and all kinds of unhygienic contact. The intelligent building use Hunt facial recognition camera to recognize people and make access more convenient and effective. Doors and gates open for employees in front of access entrance during its walk-through. People do not need to stay for seconds or look into the camera directly. People who have not registered his/her face in database will be blocked before entry. Visitor will go to the reception kiosk to add his/her face for a temporary pass of restricted floors. The gate does not get disturbed by people who stay nearby or pass by. It works also robustly to variant lighting conditions in the building, such as sunny window or dark stairs. Integrated NVR is installed in reception desk in search of suspicious individual in recordings by facial recognition results. Once a suspicious face is added to a blacklist, security will get alarming message if he/she comes back again.