Gesichtserkennung

Distinguish one-to-one verification from one-to-many search. Comparing a new image with one enrolled image has different operating conditions from searching a large gallery. The gallery size, threshold, and image quality affect how results should be interpreted. Evaluate false matches and false non-matches separately. Lighting, pose, resolution, age differences between images, and the population represented in the evaluation can change performance. NIST’s evaluations document why the algorithm, task, and dataset all matter. Review the intended use and applicable privacy and biometric requirements before deployment. Collection, retention, consent, access, and the ability to challenge an outcome need explicit treatment. A technically available system is not automatically appropriate for every setting. Use independent corroboration and appropriate human procedures for consequential decisions. A candidate list should remain a lead to assess under a valid process, not a definitive identity declaration. Report the evaluated conditions and uncertainty instead of advertising a single universal accuracy figure.