(If you missed Part 1, which introduced Amulet Voice Kinect, read it here.)
So after deciding to see if HaarCascades would work at all with the depth-stream from Kinect, I figured I needed to give the first test the best chance of success. There was no point making a half-hearted effort, have it fail and then having to have another go because I wouldn’t have known if the failure was down to some fundamental problem with using the depth-stream with HaarCascades or just because I had poor HaarClassifiers. To give the test the best chance of success I would need several thousand depth images containing the object that I needed the classifier to recognise and several thousand negative images not containing the object. I settled on 2000 of each.