Ask Your Question

Revision history [back]

What the progress does is the follwing, based on %SMP

  • %SMP stands as you say for percentage of samples
  • During the first stage a single feature is used to classify all images, you will get 100% usage of the samples at that moment.
  • Secondly, all the samples that were classified wrong by the feature, are treated in the next feature, for again classifying positive and negative samples.
  • This continues, so the percentage shows the amount of elements the weak classifier in the previous step did not succeed to classify correctly.

Does this makes any sense?