I have implemented the AdaBoost sequence algorithm and currently, I am trying to implement the so-called Cascaded AdaBoost, basing on P. Viola and M. Jones's original paper. Unfortunately, I have some doubts, connected with adjusting the threshold for one stage. As we can read in the original paper, the procedure is described in literally one sentence:
Decrease threshold for the ith classiﬁer until the current cascaded classiﬁer has a detection rate of at least d × Di − 1 (this also affects Fi)
I am not sure mainly two things:
What is the threshold? Is it 0.5 * sum (alpha) expression value or only 0.5 factor?
What should be the initial value of the threshold? (0.5?)
What does "decrease threshold" mean in detail? Do I need to iterative select a new threshold e.g. 0.5, 0.4, 0.3? What is the step of decreasing?
I have tried to search for this info on Google, but unfortunately, I could not find any useful information.
Thank you for your help.