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Python and Java API / Re: Creating and Managing Multiple Chunks
« on: December 18, 2017, 07:44:54 PM »
I made some tests using geotagged photos (from the drone's onboard GPS system) regarding preselection.
With these parameters:
High Accuracy (keeps 100% of each image, not upscales or dowscales)
Total cameras (photos): 155 geotagged
Key points = 10,000 (not that much to optimize time in the processing)
Tie points = 0
-----------------------------------------------------
No preselection
-----------------------------------------------------
148 aligned cameras of 155
Points 50,476 of 55,628
RMS reprojection error: 0.115293 (0.602434 pix)
Max reprojection error: 0.348031 (19.6074 pix)
Mean key point size: 4.19666 pix
Effective overlap 2.58956
Match time: 00:23:56
Align time: 00:01:46
Total time: 00:25:42 -- compatible time with the Reference preselection only
-----------------------------------------------------
Generic preselection only
-----------------------------------------------------
148 of 155 aligned cameras
Points 50,780 of a total of 54,274 possible
RMS reprojection error: 0.115442 (0.60689 pix)
Max reprojection error: 0.348413 (19.5868 pix)
Mean key point size: 4.19952 pix
Effective overlap: 2.59327
Matching time: 00:37:49
Alignment time: 00:01:49
Total time: 00:39:38
-----------------------------------------------------
Reference preselection only
-----------------------------------------------------
148 of 155 aligned
Points 50,670 of 54,789
RMS reprojection error: 0.115329 (0.610028 pix)
Max reprojection error: 0.348384 (20.2262 pix)
Mean key point size: 4.19839 pix
Effective overlap: 2.59209
Matching time: 00:23:48
Alignment time: 00:01:49
Total time: 00:25:37
-----------------------------------------------------
Generic + Reference both selected!
-----------------------------------------------------
148 of 155 aligned
Points 50,790 of 54,269
RMS reprojection error: 0.115142 (0.605183 pix)
Max reprojection error: 0.347645 (19.5746 pix)
Mean key point size: 4.19816 pix
Effective overlap: 2.59146
Matching time: 00:18:39
Alignment time: 00:02:07
Total time: 00:20:46
That justifies the code to use generic + reference if there's geotagged photos. And if not, no preselection.
With these parameters:
High Accuracy (keeps 100% of each image, not upscales or dowscales)
Total cameras (photos): 155 geotagged
Key points = 10,000 (not that much to optimize time in the processing)
Tie points = 0
-----------------------------------------------------
No preselection
-----------------------------------------------------
148 aligned cameras of 155
Points 50,476 of 55,628
RMS reprojection error: 0.115293 (0.602434 pix)
Max reprojection error: 0.348031 (19.6074 pix)
Mean key point size: 4.19666 pix
Effective overlap 2.58956
Match time: 00:23:56
Align time: 00:01:46
Total time: 00:25:42 -- compatible time with the Reference preselection only
-----------------------------------------------------
Generic preselection only
-----------------------------------------------------
148 of 155 aligned cameras
Points 50,780 of a total of 54,274 possible
RMS reprojection error: 0.115442 (0.60689 pix)
Max reprojection error: 0.348413 (19.5868 pix)
Mean key point size: 4.19952 pix
Effective overlap: 2.59327
Matching time: 00:37:49
Alignment time: 00:01:49
Total time: 00:39:38
-----------------------------------------------------
Reference preselection only
-----------------------------------------------------
148 of 155 aligned
Points 50,670 of 54,789
RMS reprojection error: 0.115329 (0.610028 pix)
Max reprojection error: 0.348384 (20.2262 pix)
Mean key point size: 4.19839 pix
Effective overlap: 2.59209
Matching time: 00:23:48
Alignment time: 00:01:49
Total time: 00:25:37
-----------------------------------------------------
Generic + Reference both selected!
-----------------------------------------------------
148 of 155 aligned
Points 50,790 of 54,269
RMS reprojection error: 0.115142 (0.605183 pix)
Max reprojection error: 0.347645 (19.5746 pix)
Mean key point size: 4.19816 pix
Effective overlap: 2.59146
Matching time: 00:18:39
Alignment time: 00:02:07
Total time: 00:20:46
That justifies the code to use generic + reference if there's geotagged photos. And if not, no preselection.