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Topics - Jobbo90

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Camera Calibration / Difference in camera calibration values
« on: October 29, 2020, 02:37:29 PM »
Hi All,

Following up on some discussions I found here I started diving into two projects I have over the same area but with 9 months difference between acquisition. Both projects were acquired with the same DJI mavic pro 2 and the same flight paths planned in Lithci (nadir and off-nadir pictures at each location). The only difference is the flight height which was 50 meters in 2019 and 75 meters in 2020 (relative windy conditions, so the ensure sufficient overlap I dicided to increase the flying height). The results showed here contain roughly 50% of the pictures processed inAgisoft metashape 1.5.2 (I'll try 1.6.x soon as well!). All alignments are at 'standard' settings:
high accuracy, generic preselection ON, reference preselection ON, key point limit 40.000, tie point limit 4.000, adapative camera model fitting ON.

I started notcing I considerable doming effect in the 2020 data and found in other discussions here that this might be related to the automatic camera calibration performed by Agisoft. When I look at the estimated calibration camera's I get confused.  So for 2019 all seems to be fine with estimated f at 4289.5 (intial at 4256), and cx,cy at 20 and -49 respectively and b1 and b2 at 0.23 and 0.38. Allthough I wonder why the estimated f is different and if so if the difference is acceptable. (hopefully the example images are clear!)
For 2020 is becomes messy: estimated f is at 3366.8, cx and cy at 63.8 and 1556.1 respectively, and b1 and b2 are -66 and 22.  Remember, these are the same drone and flight lines (except the heigt). So to check if something else changed I looked at another fleight campaign I did around the same date in 2020. Here the camera calibration values are way better: estimated f at 4256 (it is the same as the intial...) and cx and cy at 17 and -27 respectively. b1 abd b2 are at -22 and -0.15, so only b1 is still way off.

So my questions is where these difference come from, is it camera settings during flying or something else? And more specifically what can I do to improve the alignment of the 2020 data?
I already read something about enabling rolling shutter before alignment (this doesn't improve the 2020 dataset) :

Also trying to estimate the camera calibration parameters beforehand and 'fixing' them seems to be an option:
Just wondering if that is going to help?

Some additional info:
both datasets are part of a larger set that also contains 20 - 25 GCP markers (dGPS quality) that do help for the overal quality of the outputs. Yet especially the DEM suffers from significant doming in the 2020 dataset, but also the orthophoto is distorted to the large noise, even after gradual selecting tie points with relatively strict reprojection error values, reconstration uncertainty and projection accuracy filters. Also the lay-out of the markers is not optimal due to limited accessibility at the boundaries (muddy intertidal area). This is why i'd like to see if there is improvements possible in the allignment and camera callibration.

Curious to see if there is somebody who can direct me towards a potential solution for the 2020 dataset!

General / Mis-alignmened pictures in UAV project
« on: August 08, 2019, 03:15:01 PM »
Hi All,

I have UAV(Mavic Pro2) project where a part of my pictures don't align or align in some sort of sphere shape. Because it is only part of my picterues that don't align I'm confident that the overlap in my flight plan is sufficient. The pictures not aligning contain, beach forest and water so i'm guessing part of the problem is relatd to the surface cover types. I'm just curious if it is possible to play around with the Agisoft settings to force metashape into alignment. In the near future i'd like to return to the location and where possible optimize the flight plan to ensure correct alignment

Project details:
- .dng pictures (relative 'dark' if you ask me?), a subset of 280 pictures of which 120 are not aligning propperly. The original dataset contains over 1100 pictuers wich are aligning just fine, just this spatial subset is not working.
- On each location a nadir and off-nadir picture. Locatoins are spaced 40 meters apart and flown at 100m, despite the exif metadata suggestin 65 meters.

What kind of steps would you recommend to try? I played around with different levels of accuracy, watermasks and all the other alignment options. Also I'm wondering if I could do some image processing or if it helps to explose the camera calibration possibilities?

Enclosed there is a picture of the resulting alignment test and a sample picture.

Tahnks for your comments!

General / Import Camera Locations from xml file
« on: April 24, 2018, 04:52:37 PM »
Hi All,

I have a .xml file containing all video and photo locations (see attachment) from a drone that's been used for mapping and video surveillance.

What is the best way for me to acquire the relevant photo locations for aligning and building a digital elevation model?

The new flight is stored like this:
<ori yaw="+179.40" pitch="-090.00" roll="-004.41    " />
   <time value="2018:04:20 14:43:35"/>
   <note par="Flight" value="0001    " />
   <time value="2018:04:20 14:47:07"/>
   <note par="Flight" value="0001    " />
   <time value="2018:04:20 14:47:52"/>
   <gps lat="+05.90003016" lng="-055.22443772" alt="-0069.752" />

following by all the information from pictures in the following format:
<ori yaw="+124.65" pitch="-090.00" roll="-003.80    " />
<image path="D:\DCIM\100MEDIA\AMBA1124.jpg">
   <time value="2018:04:20 14:47:55"/>
   <gps lat="+05.90003016" lng="-055.22443772" alt="-0069.752" />

As far as I can tell the images are not stored with an EXIF like format containing the locations but rather have an separate file containing the locations. I also tried to change the relative pathnames with the locations of the pictures. Do I need to rewrite the file in the described .csv format in order to attach the locations to the pictures (tideous work :-X)?


General / Dense cloud or Sparse cloud?
« on: January 17, 2017, 10:06:10 AM »
Hi All,

I'm experimenting around with Agisoft and have a bit of a theoretical question.

I'm working with a close range photogrammetry project (300-400 pics), taking pictures of geomorphology of an area compromosing 2 by 8 meters. I used a Canon EOS 1300D camera with a focal length around 40mm resulting in high density point clouds.
Now i'm wondering if it is worth to bypass the build-dense cloud step for computation speed and data reduction purposes, this will result in building a mesh based on the sparse cloud.

- How would this affect the accuracy of the final DEM (I'm trying to reach mm accuracy)?
- What is it exactly that the dense cloud step does?
- If I for example run algnment at high settings I already end up with 9.5 million points on such a small area, anybody can tell if this is sufficient?

At some stage i'd like to test how the bypassing of the dense cloud affects the accuracy, but at the moment I don't have sufficient time and resources available so im wondering if other already considered these steps.

Curious about your thoughts!

General / Orientation in model with arbitrary coordinate system
« on: January 09, 2017, 12:49:21 PM »
Hi all,

Somewhere in my workflow i'm causing my 3D model to be inverted. I have a model with 400 photo's and 7 groundcontrol points measured in a arbitrary coordinate system with a Total Station (need high accuracy(<5mm) points!). I worked with Agisoft before, but this is the first time I work in an arbitrary coordinate system instead of world coordinate system
X range: 29.7664 - 70.0173 meter
Y range: 15.7528 - 47.3623 meter
Z range: 18.912 - 64.4892 meter

I need a DEM and orthophoto that are overlying each other to calculate volume of a part of the model (in ArcGIS for example). After alligning the photo's I placed the markers in the photo's and model and calculated the dense cloud and mesh/texture. I think the problem is related to the moment in my workflow where I calculate camera locations based on the coordinates? My cameras are unchecked and my markers are checked when I calculate the dense cloud, i'm not sure if this is correct.

Hopefully somebody is able to shed some light on my workflow or has some examples that also work with arbitrary coordinate systems.

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