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BriefCam White Papers

Impact of Masks on BriefCam Face Recognition

Last Updated: 1 minute read
Version2024r2
LanguageEnglish

The performance of BriefCam facial recognition on people wearing face masks, showed an expected drop in reliability due to drops in face extraction and face matching accuracy. This is because a facial mask covers a significant part of the face and the algorithm has fewer facial landmarks to analyze.

Therefore, although BriefCam’s face recognition performs correctly on some instances of masked faces – it will be less accurate and less reliable for most operational scenarios.

Face Mask Detection Guidelines

Like in Face Recognition, the best results for face mask detection are achieved when the camera is at eye-level, at a shallow angle, and with no occlusions and good lighting.

Face mask detection requires a captured face quality of at least 1-star. This also means that the face resolution should be more than 40x40 pixels across the face.

Accuracy should be above 90% in scenes with good conditions (good lighting and resolution as well as a small pitch and yaw of the faces).

Examples of Conditions
Face mask bad lighting.png

bad lighting and resolution

Face mask bad angle.png

bad angle (yaw) but good quality

Face mask bad quality.png

bad image quality and angle

Face mask bad resolution.png

bad resolution, quality, and illumination (and a person with stubble)

Face mask nonface.png

non-face recognition quality

Face mask good 1.png

good quality (some tough angles)

Face mask good 2.png
Face mask good 3.png