Remote identification

Application

Remote selfie-based identification and authentication using the front camera of a mobile phone in banking systems, exchanges, municipal portals, etc. Top priority is to ensure accurate identification and prevent any errors.

Use case requirements

• One face in the frame, minimal likelihood of side views
• Images of faces are of significant size (up to 80% of the frame area)
• High noise tolerance in photos due to poor lighting or low-quality cameras
• Image type for detection and identification is "BORDER" or "MUGSHOT" (according to NIST), which corresponds to QAA totalscore >= 51%

Recommended configuration files

• remote_identification_q1.xml
• remote_identification_q2.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: processing.services.service 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.

   Example

   configs:
       capturer:
           name: remote_identification_q1.xml // name of the Face SDK configuration file

2. Open the ./cfg/platform.values.yaml file in OMNI Platform distribution, find the capturer configuration object (path to the object: generic.capturer) and enter the values for the fields of the capturer object.

   Example

   generic:
       capturer:
           name: remote_identification_q1.xml // name of the Face SDK configuration file

3. After editing the files, save them and update OMNI Platform in the cluster using the command:

   ./cli.sh image-api install
   ./cli.sh platform install

Benchmark results

Capturer configuration file	Time to detect one frame (ms)	Detection accuracy (0 to 1)
remote_identification_q1.xml	1040	0.977
remote_identification_q2.xml	75	0.97