Time to train a cascaded classifier?

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Thank goodness, I am already using a 64-bit architecture. 6 parallel classifiers training is somewhat a consolation - but approximately how long would the training be for one classifier? Let's say I only have 6 to train... how long approximately do you think the time range should be for a single training session?

I never trained multiple classifiers in parallel, so I really don't know. I can tell you that training a haar classifier with 600 positives and 1500 negatives shouldn't take a very long time, maybe half a day, possibly less, depending on your parameters. You should try it yourself and check if the time it takes is acceptable.

Thanks very much! I just noticed something else, you understood my 60x60 resolution requirement as being related to my sliding detection window. That's correct. But is my image resolution reasonable? Is 480x320 reasonable or unnecessarily large? The final testing data won't have objects as big as 480x320, although the images and videos themselves maybe large.

Im not sure I understand what you are saying. If you are talking about performing detection in 480x320 images than that is no unreasonable at all. Many people use classifiers to perform detection in 640x480 images, and more.

Oh yes I should have clarified - I was referring to the images used as training samples for the classifier, not for testing and final detection. The reason I am asking this is because in my understanding, having large images to train a classifier makes the training take longer. So I was wondering about 480x320 in terms of the image resolution for training samples - is that unnecessarily large, given that the objects I will be detecting in the end are unlikely to be that large.