time to refine

we shot more footage over the weekend and ran our algorithm on it. this time we were in regents parking lot. the first set of videos was unusable because there were some branches in the way. we relocated and took a second set of videos which looked fine.
after running our current code on the second set, we found that the algorithm is currently making the assumption that car size would be the same. we had avoided using size in determining the type of a blob, but getting the blob in the first place relied on it being a particular size. because of this, we created some goals and compromises:

1. better classification
1. using object size with correction for foreshortening
2. better object tracking
1. be more forgiving when an objects class changes, call it the same object
2. keep a history of the objects class at each frame and use that to update the overall class
3. video will be shot from AP&M only until algorithm can be generalized