A comparative study of data fusion strategies in face verification

In this paper, the merits of fusing colour information in a face verification system is studied. Three different levels of fusion, namely, signal, feature and decision levels are considered. The study is performed on a fisherface-based (LDA) verification system considering the Gradient Direction metric as the scoring function. We show that almost all the fusion methods enhance the performance of the system. However, despite the common use of the fusion at the signal level realised by creating intensity images, the other fusion methods specially the decision level fusion using score averaging are more effective.