1. A method for training an image classifier, comprising: dividing a set of training images for training a classifier into a positive-example sample set and at least two negative-example sample sets; determining, for each of the at least two negative-example sample sets, a feature set for differentiating the positive-example sample set from the negative-example sample set; and performing training using the feature set determined to obtain a classifier.