Human Detection Based on Multi-classifiers in Static Image

In this paper, we introduce Haar feature firstly, and then interpret Adaboost arithmetic which is used in training classifier.The false positive rate of this arithmetic is too high although the detecting rate is so high.In order to maintain detecting rate and reduce false positive rate, we train another two local classifiers: one is head-shoulder classifier, the other is legs classifier.The experiment shows the new method not only have high detecting rate but also can reduce false positive rate.