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Version: 2.1.0 (latest)

Cooperative Recognition in Access Control Systems (ACS)



Time and attendance systems and corporate access control systems utilizing biometric terminals or cameras, primarily deployed in well-lit environments. Top priority is ensuring accurate identification without any errors.

Use Case Requirements

  • Frames taken by a camera installed in a room with stable lighting
  • One face in the frame, ensuring direct eye contact with the camera
  • Image type for detection and identification is "BORDER" (according to NIST), which corresponds to QAA totalscore >= 51%
  • access_control_system_one_face_q1.xml
  • access_control_system_one_face_q2.xml
  • access_control_system_one_face_q3.xml

How to Configure

1. Open the ./cfg/image-api.values.yaml file in Image API distribution, find the capturer configuration object (path to the object: name.configs.capturer) and enter the same values for the fields of the capturer object in each detection service: face-detector-face-fitter, face-detector-liveness-estimator, face -detector-template-extractor.


name: access_control_system_one_face_q2.xml // name of the Face SDK configuration file

2. After editing the file, save it and update Image API in the cluster using the command:

./ image-api install

Benchmark Results

Capturer configuration fileTime to detect one frame (ms)Detection accuracy (0 to 1)