Rank-based score normalization framework and methods for implementing same

摘要

A rank-based score normalization framework that partitions matching scores into subsets and normalize each subset independently. Methods include implementing two versions of the framework: (i) using gallery-based information (i.e., gallery versus galleryscores), and (ii) updating available information in an online fashion. The methods improve the detection and identification rate from 20:90% up to 35:77% for Z-score and from 25:47% up to 30:29% for W-score.