SAFR facial recognition solutions for live video offer accurate, fast, unbiased face recognition and additional computer vision features. SAFR version 3.4’s AI-powered liveness detection can quickly (within 0.3 seconds) and accurately (95.27 percent true positive rate) verify that a live person is in front of any standard RTSP or USB camera, and not a photo or video clip being presented. In version 3.4, the SAFR algorithm analyzes texture and context, based on the RGB visual spectrum field from a standard 2D camera — be it an IP camera embedded in an access control terminal, an ATM camera, or a USB or laptop camera used to authenticate the user. It also has the ability to automate alerts to security personnel when a spoofing attempt or a fraudulent attempt to gain access is detected. The new version also allows security personnel to set specific thresholds for liveness that allow them to balance end-user convenience and specific levels of liveness veracity they require, depending on use cases. With SAFR 3.4, users can view the video and liveness analysis results in real-time or review event-based history records. SAFR now provides SMS alerting functionality for Windows customers and integrated out-of-the-box for Cloud customers.
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