FUSION OF CLASSIFIERS FOR ILLUMINATION ROBUST FACE RECOGNITION

In this paper the problem of face recognition under variable illumination conditions is considered. Most of the works in the literature exhibit good performance under strictly controlled acquisition conditions, but the performance drastically drop when changes in pose and illumination occur, so that recently a number of approaches have been proposed to deal with such variability. The aim of this work is twofold: first a survey on the existing techniques proposed to obtain an illumination robust recognition is given, and then a new method, based on the fusion of different classifiers, is proposed. The experiments carried out on different face databases confirm the effectiveness of the approach.