Concept of Cascade Classifier

I am trying to undrestand conceptually how does Cascade Classifier training works in OpenCV using LBP. I understand that AdaBoost is used for choosing weak classifiers and combining them to make a strong classifier. I also understand that LBP is used as visual descriotor of features. But the thing I could not find out is how are weak classifiers actually created from LBP? Is there any learning algorithm used, like Support vector machine? Thanks for help.