On Wed 05-Jan-2011 at 01:05 -0800, kfj wrote:
On 4 Jan., 23:52, Bruno Postle <[email protected]> wrote:
Usage: cpclean [options] input.pto
CPClean uses statistical methods to remove wrong control points
Bruno, maybe you can help. You may have noticed my quick-shot Python
script to remove all but the N 'best' CPs for each image pair. Now
while in principle I'm happy with it, there is a fundamental problem:
my 'distance' calculation is wrong. I use the coordinate distance in
the panorama, but of course this strictly only works for mosaics, and
otherwise I should use the distance on the pano sphere.
You could use PToptimizer which writes all this statistical
information about control point errors to the project file. Though
you have to clean a Hugin project file to make it acceptable to the
panotools parser in PToptimizer.
There are two tools by Iouri Ivliev in Panotools::Script to help
with this, unfortunately I have never had a chance to play with
them (it would be really useful if somebody could evaluate all this
stuff and report their experiences):
ptsed is a command-line editor for .pto projects, amongst other
things it will clean a .pto file so it can be read by
panotools/PTmender/PToptimizer.
ptscluster is another statistical filter for control points (like
ptoclean and cpclean), it uses the information in the PToptimizer
output and tries to leave a spread of control points rather than
just deleting the 'worst'.
I could make a temporary pano with equirect output and 360X180 fov,
then I could calculate the distance on the sphere from the polar
coordinates. But of course this is clumsy; maybe you can think of a
more elegant way?
You could reimplement a panorama transformation and measure the
angular distance directly, this isn't so difficult (there is one of
these in Panotools::Script used by ptoclean).
--
Bruno
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