Two-step calibration method for multi-algorithm score-based face recognition systems by minimizing discrimination loss
Nanang Susyanto, Raymond N. J. Veldhuis, Luuk Spreeuwers, Chris A. J. Klaassen · 2016
We propose a new method for combining multi-algorithm score-based face recognition systems, which we call the two-step calibration method. Typically, algorithms for face recognition systems produce dependent scores. The two-step method is based on parametric copulas to handle this dependence. Its goal is to minimize discrimination loss. For synthetic and real databases (NIST-face and Face3D) we will show that our method is accurate and reliable using the cost of log likelihood ratio and the information-theoretical empirical cross-entropy (ECE).