The "end result" for knowing where everything is on the field is for path planning. If you're interested:
https://www.dropbox.com/sh/uvmzxrgz8...Bz8k6p_pmR_Zua
all we need to know is where the thing are on the field in some coordinate system, then input their coordinates into our path finding as obstacles. Right now I can track them using a depth camera, then I do a linear transformation between the camera's coordinates (3d coordinates with camera being the origin) to the field coordinates (where the bottom left corner is the origin). By using an aerial camera, it eliminates the need for the depth map, which means on less sensor on our robot. And as a bonus, it can see the whole field, unlike a depth map.
As for your idea, we don't need it, though it is clever. For the past three years, we have been able to calculate where we are on the field solely from the vision tapes. (See also:
http://www.chiefdelphi.com/media/photos/38819 this is a pose estimation. It knows where we are in 3 dimensions with respect to the center of the top hoop, as well as how rotated we are in pitch roll and yaw). I still want to try out your method though. I see extreme value in it. The only downside is that you'd have to set it up at competition, which could be problematic.