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OpenCV AdaBoost - Obtaining Optimal Stage Threshold

Hey guys,

I came across Adaboost in OpenCV and would like to know more about it. I have a good intuition about the algorithm, thanks to the numerous tutorials in the web. But there is this one thing I am not able to catch and would really be grateful if someone could help.

The parameters,

dmin -> minimum acceptable detection per cascade stage

threshold -> Parameter tweaked to make sure that dmin is honored.

fi -> False positive rate per cascade stage evaluated at the current threshold

fmax -> Maximum acceptable false positive rate per cascade stage

are seriously creeping me out.

It would be really helpful if someone can point me towards some resource so that i can understand how threshold is estimated such that dmin holds (so that i can update fi for each iteration and exit loop when it falls below fmax thereby having a strong classifier).

I am following Zhu and Avidan's paper (Refer page 3 - Algorithm pseudocode).

Please comment if I need to update my question with any more details.

Hoping to get help. Thanks for trying.


Prasanna S

(Someone please do tell me how to use subscript and superscript while typing)