It is said “4916 positive training examples were hand picked aligned, normalized, and scaled to a base resolution of 24×24. 10,000 negative examples were selected by randomly picking sub-windows from 9500 images which did not contain faces.” In the paper “Robust Real-Time Face Detection by Paul Viola & Michael Jones”
My question is what do they mean about hand picked aligned, normalized, and scaled to a base resolution of 24×24?
Does “hand picked aligned” mean they have 4916 positive images of 4916 different faces?
Does “normalized” mean each of the 4916 images have the same features[file size, file type, picture color(gray scale/colored)]?
Does “scaled to a base resolution of 24×24” mean each of the 4916 images are re-sized to 24×24 pixels?
Thanks for your time!
Not necceseraly distinct – but yes, they gave 4916 different photos of faces. The faces were found manually by a “human expert”.
They only used a grey-scale pixels, normalized means they made sure there is no “black” and “white” pictures. If a picture was very dark – it was automatically brightened, and if it was not dark enough – it was darkened. This is done by an automatic component easily.
Yes, they made sure each “face” is exactly 24×24 pixels by applying some processing on the picture.