Comparison of Confidence Measures for Face Recognition

This paper compares different confidence measures for the results of statistical face recognition systems. The main applications of a confidence measure are rejection of unknown people and the detection of recognition errors. Some of the confidence measures are based on the posterior probability and some on the ranking of the recognition results. The posterior probability is calculated by applying Bayes' rule with different ways to approximate the unconditional likelihood. The confidence measure based on the ranking is a new method, that is presented in this paper. Experiments to evaluate the confidence measures are carried out on a pseudo 2-D Hidden Markov Model based face recognition system and the Bochum face database.

• Type: Conference
• Year: 2000
• Where: FGR
• Authors: Stefan Eickeler, Mirco Jabs, Gerhard Rigoll
• Keywords: Biometrics, Confidence Measures, Face Recognition, FGR 2000, Posterior Probability