Face Recognition Vendor Test 2002 Performance Metrics

Abstract

We present the methodology and recognition performance characteristics used in the Face Recognition Vendor Test 2002. We refine the notion of a biometric imposter, and show that the traditional measures of identification and verification performance, are limiting cases of the open-universe watch list task. The watch list problem generalizes the tradeoff of detection and identification of persons of interest against a false alarm rate. In addition, we use performance scores on disjoint populations to establish a means of computing and displaying distribution-free estimates of the variation of verification vs. false alarm performance. Finally we formalize gallery normalization, which is an extension of previous evaluation methodologies; we define a pair of gallery dependent mappings that can be applied as a post recognition step to vectors of distance or similarity scores. All the methods are biometric non-specific, and applicable to large populations.