Boosted ECOC ensembles for face recognition

The error correcting output coding (ECOC) approach to classifier design decomposes a multi-class problem into a set of complementary two-class problems. In this paper ECOC is combined with boosting using decision tree base classifiers to solve two problems in face recognition. Boosted ECOC ensembles using decision stumps and C4.5 classifiers are compared for face identification and verification.