found this nice object detection mantra from a user called HCK:
Poor evaluation results + good training results + small number of weak classifiers + much training data = too uniform data.
Poor evaluation results + better training results + large number of weak classifiers + much training data = data has too much variation.
Poor evaluation results + poor training results + large number of weak classifiers + much training data = weak classifiers are too weak.
