UNV OET-213H-BTM32 | Face/Forehead Recognition Access Control Terminal
Support non-contact detection, support warning people with abnormal body temperature Support body temperature detection and personnel information binding, which can quickly confirm personnel information and do body temperature detection Support configure temperature detection threshold value, and personnel access authority can be configured through temperature detection threshold value Deep learning algorithm model based on UNV independent intellectual property rights, face recognition accuracy rate > 99%, false rate < 1% Built-in deep learning dedicated chip, supports local offline recognition, 10,000 face capacity, face white list (1∶ N) Fastest recognition time 0.2 seconds, various model merge mode are used to reduce false rate and increase pass rate WDR, 2MP (1080P) low illumination wide-angle camera and F1.6 large aperture lens for capturing high quality image with various complex lighting scenes Support anti-spoofing detection based on deep learning algorithm, effective against fraud such as photo and video Support face metering and human metering for fast adapting to ambient light Suggested height for face recognition: between 0.8m and 2.2m,face recognition distance: 0.2m to 2.9m Support screen sleep mode, keep the minimum brightness to prevent glare at night Support add up to 6 photos of the base library for a single person Support video capture, support ONVIF protocol Support face, card, and password authentication to control door open Built-in 4G EMMC front end storage, stable and reliable, up to 8,000 events capacity (with images) Support tamper protection, support door opening timeout, support time exceeding alarm, support keeping door opening while fire alarm active
Specifications
| Return Shipping Will Be Paid By | Buyer |
| All Returns Accepted | Returns Accepted |
| Item Must Be Returned Within | 30 Days |
| Refund Will Be Given As | Money Back |
| Model | OET-213H-BTM32 |
| MPN | OET-213H-BTM32 |
| Brand | Uniview |
Support non-contact detection, support warning people with abnormal body temperature Support body temperature detection and personnel information binding, which can quickly confirm personnel information and do body temperature detection Support configure temperature detection threshold value, and personnel access authority can be configured through temperature detection threshold value Deep learning algorithm model based on UNV independent intellectual property rights, face recognition accuracy rate > 99%, false rate < 1% Built-in deep learning dedicated chip, supports local offline recognition, 10,000 face capacity, face white list (1∶ N) Fastest recognition time 0.2 seconds, various model merge mode are used to reduce false rate and increase pass rate WDR, 2MP (1080P) low illumination wide-angle camera and F1.6 large aperture lens for capturing high quality image with various complex lighting scenes Support anti-spoofing detection based on deep learning algorithm, effective against fraud such as photo and video Support face metering and human metering for fast adapting to ambient light Suggested height for face recognition: between 0.8m and 2.2m,face recognition distance: 0.2m to 2.9m Support screen sleep mode, keep the minimum brightness to prevent glare at night Support add up to 6 photos of the base library for a single person Support video capture, support ONVIF protocol Support face, card, and password authentication to control door open Built-in 4G EMMC front end storage, stable and reliable, up to 8,000 events capacity (with images) Support tamper protection, support door opening timeout, support time exceeding alarm, support keeping door opening while fire alarm active
