Hi!
I trained a classifier to detect a MacBeth colorchart which is an artificial pattern and should be easy to detect. Training was done detecting haarfeatures from 1500 negatives and 4000 positives using bg photos from google (http://tutorial-haartraining.googlecode.com/svn/trunk/data/negatives/) that were similar to the environment where the pattern is most probably to be found.
The statistics of the training seemed to be very reasonable:
It went through all 10-stages and produced a 33kb XML cascade description file.
However when I try to find the pattern, it detects all sorts of things:
Does anyone have an idea how to improve the settings or properly find that pattern?