1. A method for adapting a boosted classifier to new samples, comprising the steps of: training a boosted classifier using initial samples, in which the boosted classifier is a combination of weak classifiers; and updating adaptively, each weak classifier of the boosted classifier, by adding contributions of new samples and deleting contributions old samples.