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image questions in regards to training cascade classifier

So far I have created two LBP classifiers that do a decent job of identifying the shapes I need identified however, I would like to increase the accuracy and I have the following questions:

  1. Should all the positive and negative images be of the same size? i.e. 64 x 64 or 32 x 64 etc...
  2. If #1 is a no, do all the positive images or all the negative images have to be the same size or ratio?
  3. Should the positive image be cropped to only include what I am looking for or should it have some background ?
  4. Should the negative image be totally different (ex: out of context) from the positive or should it be similar (ex: display the background but not the positive image)
  5. Are there any rules of thumb on how many images I should use. So far I have used 1000 positive and 1000 negative.
  6. Does image orientation play any role i.e. left to right vs right to left?

Thanks in advance WGB