[GRASS-user] align large number of images in a automated way

[Terry Duell]

On Thu, 31 Jul 2014 01:15:54 +1000, Markus Neteler <neteler at osgeo.org>  
wrote:

> Dear Milton,
>
> I made a quick test with the sample data you sent to me:
>
> autopano-sift-c output.pto dir_2014_002_17_1.jpg dir_2014_002_16_7.jpg
> [...]
>   555 keypoints found
> [...]
> Filtering... (dir_2014_002_17_1.jpg, dir_2014_002_16_7.jpg)
>    A. Join Filtration: 32 to 32
>    B. Score Filtration: 32 to 25
> Filtered partition [0,1] from 32 matches down to 25
>
>
> cat output.pto
> # Hugin project file generated by APSCpp
> [...]
> # automatically generated control points
> c n0 N1 x290.400812 y143.672441 X289.377092 Y142.525139 t0
> c n0 N1 x566.209025 y383.642656 X566.343984 Y383.440512 t0
> c n0 N1 x321.360169 y120.632838 X321.409832 Y120.057093 t0
> c n0 N1 x45.026134 y21.912848 X43.642776 Y22.815530 t0
> c n0 N1 x299.155503 y122.350252 X298.325028 Y122.493041 t0
> [...]
> c n0 N1 x377.501999 y142.803118 X372.855780 Y145.767751 t0
>
> So, it easily find a lot of common points (runtime of autopano-sift-c
> is 0.72 seconds on my office Linux PC). In a scripted approach you
> could match the 18,000 images against a master image or the like, then
> convert the resulting output.pto files into a text file structure
> readable by i.rectify.
>

I have run Milton's test images through a script which calls a number of  
hugin command line programs to generate control points, optimise and spit  
out remapped images. It seems to work quite well, with a mean error of 0.1  
pix and max error of 0.3 pix.

Cheers,
-- 
Regards,
Terry Duell