I am trying to find some method to detect people using only one camera 3 meters above the ground. This is a frame returned by camera:
UPDATE: Video test -> http://dl.dropbox.com/u/5576334/top_head_shadow.avi
In order to do that, first I understand that I have to perform a background-foreground segmentation. That is the easy part.
With the foreground mask, I am able to make simple operations such Hough transform to find circles, but this way only detects the 60% of heads, including many false positives.
I could use some other simple techniques like color segmentation, but I found that people heads are very different seen from above because of their hairstyle, color, amount of hair,...
Other option I have though about it is the possibility of using HOG Descriptors, or Haar-like features, but I would need an extensive database of people seen from above to train the models. I have not found anything like that.
I thought this would be a very recurrent problem, but I can not find very much about it in the literature or internet. Any help to resolve this task will be appreciated :-)
UPDATE: For more information, The goal is to implement some generic method to make pedestrian flow tracking. The first prototype will be tested in a Mall.