Visionaire Docker Hybrid is a
- 1.The Camera will perform object detection (The computation of object detection will be performed on the camera).
- 2.The Data will be sent to the Visionaire4 service in the form of JSON format and cropped images for the classifier or further processing. If the analytic assigned is FR, it will be performing the face extraction, but if the analytic assigned is LPR, it will be performing the char recognition.
- 3.The data will be processed and sent to the dashboard.
Fast processing, detection, and identification of a face from multiple video sources simultaneously in real-time.
Our Face Recognition's accuracy achieved 99.83% using the Labeled Faces in the Wild (LFW) dataset.
Ensure that it correctly recognizes the faces with certain conditions such as tilting, distracting, and some attributes/accessories like glasses and scarves.
Our Face recognition already achieved a value of 99.04% from TKDN based on the P3DN of the Indonesian Ministry of Industry (P3DN Kementrian Perindustrian Indonesia)(3869/SJ-IND.8/TKDN/8/2022).
Save on computing and bandwidth requirements by distributing the tasks between CCTV and servers.