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Messages - b3059651

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General / Reprojection Error for each point of the sparse point cloud
« on: March 08, 2015, 09:07:29 PM »
Hi all,

I would like to ask if there is any way to export the reprojection error for each point of the sparse point cloud as a separate column after X-Y-Z coordinate columns, so to visualize the error with other GIS package?
Is this feasible in python or Agisoft?

Thanks a lot for your reply in advance,


General / Re: Areal Photogrammetry with Sony Nex7
« on: February 12, 2015, 11:03:58 PM »
Hi all,
The information you provide is really useful. I would like to ask how do you test what settings are the best without flying, just checking if the image looks good?
Do you check if the edges are sharp?
I am thinking to do something similar to find the optimal settings for Sony A6000 with 16mm pancake and 20mm. The UAV is flying max. 120m above the ground and is a fixed wing. I was thinking to just replicate the distance, set a black and white target at a 120m distance and capture it with different settings, especially to check the optimal aperture for focusing to infinity at 120m.

It would be good to look on the thesis you recommend. I am based in Newcastle University and I have many Germans who can help me retrieve some results. Is it possible to send a link of the thesis?


General / Re: Image footprints in world coordinate system
« on: February 10, 2015, 03:31:42 PM »

I have sent the project with a link via sendspace and I added two photos together with the python script to help you find  the mistake.

Thanks a lot in advance :)

General / Re: Image footprints in world coordinate system
« on: February 09, 2015, 01:05:32 PM »
Thank you so much for your help. I will do another trial today and if it doesn't work I will let you know.


General / Re: Image footprints in world coordinate system
« on: February 06, 2015, 04:01:28 PM »
Hi all again,

I would like to add a comment, maybe you can help me to understand better.

Throughout the whole process while we try to determine the 3D coordinates of the image borders there is a sequence of transformations:

1. pixel coordinates of each individual image borders to image camera coordinates (according to intrinsic camera parameters)
2. from camera coordinates to chunk frame (a frame of the image block) and then
3. from chunk frame to world (3d) frame

Is this right? In the meantime intersection with the generated surface (TIN) is computed.

I hope you can help me on clarifying this.

Thanks in advance

General / Image footprints in world coordinate system
« on: February 06, 2015, 03:35:15 PM »
Hi all,

Following a previous thread ( I would like to ask 1) what is the purpose of the if statement, as seen in the attached script:

if (0 < result[1]) and (0 < result[2]) and (result[1] + result[2] <= 1):
         t = (1 - result[1] - result[2]) * vertices[v[0]].coord
         u = result[1] * vertices[v[1]].coord
         v_ = result[2] * vertices[v[2]].coord
         res = chunk.transform.matrix.mulp(u + v_ + t)
         res =

and 2) do you know if the result of the transform.matrix.mulp is the transformation of pixels to image coordinate frame after the intersection with the actual TIN?

As I a understood without the if statement the process is running for ever but still I cannot find an explanation for the conditional if. Can you please give me a feedback on that?

This script seems really useful and important because it shows the footprint but I cannot make it work with my dataset.  :(
Thanks a lot for the script, anyway.

Hi Alexey,

I tested the script and it is working well with the new Photoscan version of course. Thank you so much. My only concern is that the dictionary is not the ideal representation if I want to use the error in excel. Is there any way to convert the dictionary directly to a list?

Would something like list=photo_avg.items() work?

Thanks  a lot in advance,

General / Photoscan process and publiced articles
« on: January 12, 2015, 04:35:27 PM »
Hi all,

I would like to follow a previous discussion about the process in Photoscan. I found a nice recent article (Remondino, F., Spera, M.G., Nocerino, E., Menna, F. and Nex, F. (2014) 'State of the art in high density image matching', The Photogrammetric Record, 29(146), pp. 144-166.) where the authors explain how the different software work. I will present here some sentences of the article exactly as they are written and ask some questions in the end so to understand if this is the case of Photoscan of what they describe. 

...Nevertheless, from the autors' experience and from the achievable 3D measurement results, the implemented image-matching algorithm seems to be a stereo semi-global matching (SGM)-like method (for this study, version 0.9.0 Photoscan was used). Normally the software delivers results that are already meshed.....(pg. 151)

...PMVS employs a true-multi-image matching approach, meaning that for each object point visible in multiple images only one unique 3D point (which satisfies certain geometric conditions) is computed. On the other hand a 3D point cloud is computed for each pixel in the overlapping area of each of the stereopair in the Photoscan and SURE methods. In such cases , for n stereopairs, n 3D points corresponding to the same object point can be computed. This is particularly true in the case of large GSD and sub-pixel matching, leading to clusters of 3D points grouped near each other in the object space (but representing the same 3D point). This large number of points then can be successively averaged or statistically  reduced to a cloud of unique points, but the user needs to consider a proper workflow that takes into account the point-cloud processing requirements for point averaging, de-noising and filtering....... (pg. 161)

1. From the first paragraph: does the resulting dense point cloud represent the raw data or the vertices of the triangulated mesh with the new version of Photoscan?
2. From the 2nd paragraph: Does we actually get many points near to each other representing the same object feature when we export the final point cloud after the optimisation part? Is the point average, flitering of de-noising process part of the in-build command 'construct the dense point cloud' or we, the users, should apply a seperate process to get the average points for each object from  the multiple image-pairs?

It would be ideal if you can confirm these statements because these can help us, the users, to understand in depth the concept and of course to reinforce the reasons why we get better accuracies with Photoscan than other software when it comes to explain that in a written report.

Thanks you so much for the time reading this and replying in advance.


Thank you so much for your reply and your provided code.

Though in my University we have the previous version and since we have only educational licence there is a possibility we cannot upgrade into the newer version therefore this code might not work, right?

But I will try it and I will let you know.


Python and Java API / Export Reprojection Error of each camera station
« on: December 18, 2014, 12:53:21 AM »
Hello all,

I would like to ask if I can export the reprojections plus the reprojection error for all camera stations as a txt file with the format as follows: 
Photoname.tif, Reprojections, Reprojection error
I am searching to find a way to do it in Agisoft (without python scripting) like when it is possible to export the estimated camera stations but I cannot find it. So I assume it might be straight forward for python.

Is there any older topic for that?

I want the reprojection error for each camera station because I want to check if there is any correlation between this error and the accuracy achieved with the different number of ground control points (GCPs). So I am processing with Agisoft many times using different number of GCPs and I want to check everytime how much the reprojection error changes.

Thank you in advance for your help

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