Hi, I'm using successfully opencv traincascade module with LBP.
Still I'm not sure if my training is "logical"
I have two questions: 1.Is nneg the number of negative samples, is simply the number of training Images or is the number of training samples taken from the images?(So there could be for example 1000 neg images but 2000 samples taken from those images as neagtives)
2.FA Rate - Is it per FA/Image?So In each stage we scan the negative images and make sure that no one of them is positive(according to the desired FA)? I can ask it another way ,If the the FA is 0.5 and we have 14 stages so we have 0.5^14 error rate.Does this mean that after that the learning process is ended 'so on those negative Images the error will be 0.5^14 per frame? Actually I don't understand the training process inside the function what happens in the stage when I asked for 0.995 Det rate and 0.5 FA rate. The positive is simple and clear.But what about the neg samples?after choosing features do we run after on the neg scan them(block by block rescale and all this stuff)with the current classifier and check hat we fulfilled the stage error?
I know it's a long question' I hope for simple answer.
10x
