What is optimized FOV really?

I'm a new member of the group, and I'm looking again at Hugin and
PanoTools after a long time.

I work on a product that combines panoramic photography with a range
scanner, our website is here if you're curious:
http://www.deltasphere.com/

We take color photos using a Nikon D300 and a Nikkor 14mm rectilinear
lens, covering 360 x 150 or so with 18 photos, portrait orientation, 9
aimed high and 9 low.

We calibrate the camera and lens combination in our lab, and use a
fixed focus and F-stop.
We use the Bouguet calib toolbox to do this:
http://www.vision.caltech.edu/bouguetj/calib_doc/index.html

What I'm trying to figure out is the correspondence between the
Bouguet camera calibration and the Hugin model. I can't figure out how
the FOV that is optimized and displayed in Hugin is used to get real-
world 3D rays.

Specifically, the a, b, c distortion numbers use the normalized
radius, which is set to be 1.0 at h/2 (if h is the smaller image
dimension). This doesn't refer to real-world size or angles at all.

Hugin figures out where each photo is pointing in the world. If I want
to find out where one of the pixels in a photo is pointing, I need to
use the FOV and the distortion numbers to make a ray that points to
that pixel. Do I use the FOV before the distortion, or after?

I'm having a hard time stating this clearly, but what I'd really like
is the math used to take a 3D point as seen from the nodal point of
the panorama, and figure out which pixel it hits in a photo.

We already do this with the Bouguet camera calibration, and I have
lots of notes and a spreadsheet comparing Hugin and Bouget, but I
can't get it to quite correspond...

P.S. Thanks to Carl von Einem for pointing me to the developers list,
I didn't know it existed from looking at the wiki, and I knew this
question wasn't good for the user's list...

Thanks,
Aron

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