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Optimizing
problems
The
value displayed during optimisation is somewhat too high
First note that this value represents the average
distance between matching contral points in the resulting
panorama.Thus for a given set of images and control points,
it is proportionnal to the size of the panorama. So 2 pixels
distance for a 1000x500 panorama is bad, 3 pixels for a 3000x1500
panorama is correct (but not outstanding !)
You didn't rotate your camera around
its nodal point, and you got parallax errors (for more information,
see Panoguide article
on parallax,
and Coolpix
nodal point positions at 360texas.com).
This problem is usually more severe in tight places than
in landscape panoramas. If you can't re-shoot your panorama,
try to minimize the problem by selecting control points
in faraway features. Seams in nearby objects will be bad
though.
One (or more) of your control point
is bad. Go to the Control points tab (after applying optimizing
results). The distance between each matching control points
will be displayed. Try to delete the control points with
the highest error and replace them if necessary. Tip: since
you applied (wrong) optimizing results to your startup values,
this can prevent convergence of the optimizer after you
removed bad control points. In that case, reload your script
(you didn't forget to save it before optimization, did you
?) and delete those bad C.P. before any optimization.
The
value displayed during optimisation is much too high and/or
the hfov is obviously wrong for my lens
A few possibilities...
You selected a template that doesn't
match your situation
Your images are not in the right order.
Remember that my templates requires that you name the images
in alphanumeric order as your camera is rotated clockwise.
Some control points are very
wrong.
You try to optimize too many parameters
and your control points don't provide informations that
the optimizer can use to compute them (this should not happen
with the templates I provide...). One solution (obviously
wrong, but mathematically correct) to minimize distance
between matching control points is to reduce each image
to a point and overlap all the images : the distance will
be zero. This case can happen for example if you try to
optimize for hfov and distortion parameters (a, b and c)
with a two fisheye images 180° apart. Since all control
points you can provide are located approximately at the
same distance of images centers, the optimizer has no way
to guess these values and will probably converge towards
all 0.
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