问题
I am trying to perform Adaboost training stated by Viola and Jones in their paper on rapid object detection. However, I do not understand how to get the threshold values that will classify the faces from non faces for each of the 160k features. Is this a threshold you set manually? or is this based on some kind of maths ?
Can someone please explain the maths to me thanks a lot.
回答1:
IMO, the best way to describe what happens during threshold assignment of the weak classifiers in every boosting round is a ROC analysis of the weak classifier performance. A great introduction on ROC analysis was written by Tom Fawcett. The full algorithm that does what you want is described in Shappire and Freund`s book, section 3.4.2.
来源：https://stackoverflow.com/questions/20051796/threshold-values-for-viola-jones-object-detection