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Need explanation for viola-jones boosting

I've been trying to implementviola-jones face detection inside my project. I've read the paper too. However, i got things mixed up in my mind.

  1. I know that AdaBoost uses weak classifier (which could be any learning algorithm) to produce the hypothesis. In viola-jones system, which is the weak classifier? Is it the haar-like features?
  2. I have read the cascaded file (the xml files), i found that at each stage, a leaf has a single "feature index". What are they?