The effect of confidence errors on estimation fusion using Bayes' criterion

Information fusion can be used to combine estimates from different sources to give a single estimate of greater quality. To achieve this, it is often necessary to use confidence measures to gauge the reliability of individual estimates. This paper presents empirical results which suggest that errors in such confidence measures are important when choosing appropriate fusion strategies.