I want to train a dataset for face detection.

I'm gonna use LBP as weak classifiers and Adaboost for boosting them to one strong classifier.

I have positive and negative samples. Their size is 18x18 pixels. I'm dividing each picture to 9 sub-regions. In each block i am calculating each pixels LBP value. And count their frequency in block. So each block have 256 values as frequencies.

My question is, how can i use LBP in Adaboost? Adaboost expects a weak classifier, but LBP by itself cant classify an image. How can i modify Adaboost to select most important values from each block?