Messages

1

General / Definitions of Error (m) and Error (pix) when the marker is checked/unchecked

« on: August 09, 2023, 08:17:05 AM »

In Reference pane of Metashape, the estimated marker 3D coordinates as well as Error (m) and Error (pix) values change by just checking/unchecking markers (without retrying georeferencing or Bundle Adjustment).

This issue has been discussed in the following topics.
https://www.agisoft.com/forum/index.php?topic=11329.0
https://www.agisoft.com/forum/index.php?topic=11655.0

According to the discussions, I have understood as follows.

1. When a marker is unchecked, its estimated 3D position is that calculated by triangulation, in other terms by minimizing RMS reprojection error. The minimized value is shown as Error (pix). Error (m) shows the difference between the estimated (triangulated) position and the "source" position provided by user.

2. When a marker is checked, its estimated 3D position is that obtained by BA (i.e., by minimizing something like a weighted sum of squared reprojection errors and squared differences between adjusted and "source" coordinates). The Error (pix) and Error (m) are calculated by using the 3D coordinates obtained by BA.

However, I still have a question. Error (m) and Error (pix) as well as the estimated position change by just checking/unchecking markers even when the markers were imported after BA. The above explanation #2 cannot explain this phenomenon.

So I'd like to ask again, what happens to the estimated position when a new marker not involved (existing) in bundle adjustment (in Alignment or Optimize Camera Alignment command) gets checked.

2

Feature Requests / Tie point limit per image pair

« on: December 15, 2022, 12:31:50 PM »

Hello.
Some UAV-based flight missions take groups of photos of several different orientations.
When  "Align Photos" command is applied to such a photo set, the in-group matchings (matching among photos of the same orientations) can dominate and inter-group matchings (matching among photos of the different orientations) can be relatively few.

This is not good for the camera parameter estimation because some parameters (such as the intrinsic parameter f) cannot be estimated just by in-group matchings. If in-group matchings is dominant, the inter-group matchings may not have an enough influence (in least-squares optimization assumed).

Therefore, it would be great if the user can specify a tie point limit per image pair, namely the maximum number of feature matches allowed between two photos. This is different from the currently implemented "tie point limit" (per image).

3

Bug Reports / Incremental image alignment decreases the original matches

« on: December 10, 2022, 05:44:41 AM »

Hello. I have tested "Incremental image alignment" in Metashape Pro 1.8.4, according to the user manual.

First, after confirming that "Keep key points" is checked in Preference dialog, I have added 5 images to the blank chunk, and ran "Align Photos." As a result, image C3_2 got 3097 total and 3032 valid matches with image C3_4, as shown in one of the attached images.

Then, I have added another 5 images to the chunk. Consequently, the chunk consisted of 10 images: 5 aligned and 5 non-aligned.

After that, I ran "Align Photos" without modifying the alignment settings. As a result, the number of total and valid matches between image C3_2 and image C3_4 were decreased to 1231 and 1171, respectively, as shown in another attached image.

So it seems like the matching are reset and retried among the originally existed images too.
Although it is mentioned in a past post that "Incremental image alignment" does not decrease the original tie points, I guess the above-described behavior can decrease the original tie points as a result of decreasing original matches.

4

Bug Reports / Re: Marker reprojection error changes by checking/unchecking the marker

« on: December 25, 2019, 05:01:07 AM »

Hello Alexey,

Thanks for your reply

I think your quoted message discuss the errors for world (LSE) coordinates of markers.
I understand that estimates of marker world coordinates from triangulation are different from those from Bundle Adjustment.
Then, how may I apply the discussion to the problem I have asked here?

I infer that the displayed reprojection error of a unchecked marker is calculated by projecting the triangulated world coordinates, while that of a checked marker is calulated by projecting the world coordinates adjusted via BA.
Is my guess correct?

In addition, let me confirm a few points regarding your quoted explanation.
I have asked here:
https://www.agisoft.com/forum/index.php?topic=11329.msg52294#msg52294

Thank you.

5

General / Re: View errors - orders of magnitude changed?

« on: December 25, 2019, 04:45:03 AM »

Hello Alexey,

Thank you for the information
May I confirm the following points regarding your explanation?

In Metashape Pro (and PhotoScan Pro) versions prior to 1.5.4 estimated control point coordinates displayed in the Reference pane (and the error values as well) were calculated based on minimization of the reprojection error only

I think "minimization of the reprojection error" here means the one done in triangulation process for each point, not the one in Bundle Adjustment (optimization of intrinsic/extrinsic parameters). Right?

I believe that, in any version of Metashape so far, BA minimizes the weighted sum of "reprojection errors for valid tie points" and "estimation errors of LSE coodinates for checked markers and checked camera extrinsic parameters".

So they did not correspond to adjusted coordinates from the bundle adjustment step, and were recalculated from weighted image measurements alone.

I guess here "adjusted coordinates from the bundle adjustment step" for a control point means the sum of the observed (source) LSE coordinates and the residuals remained at the final iteration step of the optimization (BA), displayed in Chunk coordinate system. Right?

6

Bug Reports / Marker reprojection error changes by checking/unchecking the marker

« on: December 23, 2019, 10:29:40 AM »

Hello.
In Metashape versions 1.5.4 and 1.5.5 in my environment (Windows 10 64bit), marker reprojection error values, displayed in the rightmost column "Error (pix)" of Reference pane, often change by just checking/unchecking the marker, even though no camera parameter is changed.

This phenomena cannot be observed in 1.5.2 and 1.5.3, and therefore I guess it is a kind of bug.

7

General / Re: The criterion used in Key Point Limit

« on: November 14, 2019, 03:07:41 PM »

Hello Alexey,

Thank you for your reply.
Then, we will check if other measures to increase the relative weight of measured camera coordinates (i.e., decreasing camera accuracy [m] increasing tie point accuracy [pix] settings) in BA have the similar effect to enhance SfM accuracy.

8

General / Re: Tie points are not well masked in vegetation and water regions

« on: November 13, 2019, 03:02:19 PM »

I have attached the report about the CG test described above: a simple test on the “apply mask to tie points” feature in Metashape.

In addition, I have uploaded the relevant files (images and Metashape projects) here:
https://drive.google.com/file/d/13PHUnGQYcQtUmaAyPBLlW21AFQgagTTg/view?usp=sharing

I hope you and Agisoft support kindly check them out .

9

General / Re: The criterion used in Key Point Limit

« on: November 13, 2019, 10:36:48 AM »

I am sorry but in the four cases I mentioned in my first post, the Cases 1, 2, 4 and the Case 3 had different camera group settings.
When I used the completely same settings except the key point limit and alignment accuracy, the result was:

Case 1. Alignment accuracy "High" and Key point limit 50000: 0.1069 [m]
Case 3. Alignment accuracy "Low"  and Key point limit 1000:  0.0247 [m]
Case 4. Alignment accuracy "Low"  and Key point limit 3125:  0.0380 [m]

I apologize for the misleading post.
Anyway, the key point limit has a significant effect on SfM accuracy (check point errors).

In the attached Excel file I share the results of all 819 runs so far.
Runs 799, 303, and 783 correspond to the three cases listed above.

In addition, I have uploaded the reports for the three cases here:
https://drive.google.com/file/d/1D9p5wqhFJJxE_WDU1K_g_AvJgA_mp4nL/view?usp=sharing.

The version I used is Metashape Professional Version 1.5.5 build 9097 (64 bit).
Thank you for your attention.

10

General / Re: The criterion used in Key Point Limit

« on: November 13, 2019, 05:18:02 AM »

Hello Alexey,

Thank you for your reply.
I will check the 1.6.0 new feature.

Yes, it is possible if the upload size problem (the 664 images have the file size of 5.5 GB) is solved and if you give some feedback.
And if possible, could you tell what kind of keypoints are  excluded in "Key Point Limit" feature? Smaller and less distinct ones?

11

General / The criterion used in Key Point Limit

« on: November 12, 2019, 03:21:02 PM »

I have recently recognized that a very small "Key point limit" coupled with image downscaling (low alignment accuracy setting) sometimes greatly improves SfM accuracy.

But I don't find any information about what kind of criteria Metashape uses to select the features up to "Key point limit."
For example, the open source SfM software COLMAP selects the large scale features up to "max_num_features" setting.
Is Metashape using a similar criterion or combining multiple criteria including scale and distinctness?
If it is not a company secret, I'd like to know.

The situation I recognized the importance of  "Key point limit" is as follows.
For a project of 664 Phantom 4 RTK images (nadir + oblique) from 110 m altitude,  I got the following total RMS error values for 23 check points:

Case 1. Alignment accuracy "High" and Key point limit 50000: 0.8514 [m]
Case 2. Alignment accuracy "High" and Key point limit 1000:  0.4446 [m]
Case 3. Alignment accuracy "Low"  and Key point limit 1000:  0.0247 [m]
Case 4. Alignment accuracy "Low"  and Key point limit 3125:  0.4056 [m]

These are just typical examples selected from 300+ combinations of settings I have tested. The large errors in Cases 1, 2 and 4 are due to large overestimations of ground altitude, associated with the underestimations of the intrinsic parameter f. The result indicates that using large-scale & "selected" features sometimes improves the accuracy of SfM.

12

General / Re: Tie points are not well masked in vegetation and water regions

« on: November 12, 2019, 02:39:50 PM »

Hello, James.
Thank you very much for your clear and informative expalanation.

Excuse me for the delayed reply. I am preparing a test CG project to confirm that

points in unmasked images are only 'masked' if they are matched with points in the masked image.

I will report the result when ready.

As for the solutions, in my experience, the four criteria available in gradual selection are not effective in discriminating submerged (water) area.
The practical quick solution then seems to be deleting the submerged points after the alignment.
But in this case, I worry that such points may degrade the camera parameter estimation in the alignment stage and thereby induce inappropriate tie point filtering in the stage, which cannot be restoreed afterwards.
The best but time-consuming approach may be making water mask for each image using external machine-learning programs.

13

General / Tie points are not well masked in vegetation and water regions

« on: November 01, 2019, 03:57:22 PM »

Hello.
I am working with UAV photos over an area partially covered with trees and water.
I'd like to mask them out in alighment because they sometimes degrades the camera parameter estimation.
The problem is that "Mask tie points" option doesn't work well in my case.

Specifically, I still get some tie points on regions with tall vegetation or water, even when I mask the regions on at least one photo and enable the "Mask tie points" option in alignment. Those tie points are not displayed on the masked images (indicating that they are not tied with the masked images), but it's clear that they fall inside the masked area if they are projected to the masked image.
I do not observe this phenomena when I apply masks to flat regions on the ground in the same image set.

Could someone tell me why this happens?

Alexey explains about  "Mask tie points" function as:

This feature will not create any new masks, it is just meant to avoid any tie points being created beyond the masked areas.

on this page:
https://www.agisoft.com/forum/index.php?topic=11021.msg49743#msg49743
but I don't understand well what "beyond" means here.

Another problem I've got is that the tie points in regions surrounding the masked regions are reduced (thinned) by the mask. This also happens in flat regions.

I am using Metashape version 1.5.5 build 9097.
Thank you for your helps.

14

General / Why the key points change every time I run Align Photos?

« on: August 03, 2018, 01:53:21 PM »

Hello.

I have been wondering why the result of “Align Photos” command (e.g., the number and positions of points in the sparse point cloud) is different every time I run the command, even if I restart PhotoScan each time and use exactly the same setting.

Then, I have noticed that the number of the key points (feature points) detected in each image changes every time I run the “Align Photos” command. It means that the process is stochastic in its first stage: feature detection.

I understand if the optimization (e.g., bundle adjustment) process is stochastic, because stochastic strategy is sometimes useful to avoid local minima in optimization. However, I have no idea why the feature detection process should be stochastic, not deterministic.

Of course the detailed algorithm must be secret, but I would be happy if I can understand why it should be stochastic.

15

General / Re: [Help] Large error in GCPs

« on: August 03, 2018, 01:33:49 PM »

Hello ManishSahu.
I think the number of GCPs you provided is simply too small.

Just with three GCPs, it is possible to do the geoferencing.
However, it is insufficient for inclusion in the bundle adjustment (Optimise Cameras command).