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Topics - Marcel

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For the best results in Photoscan you need perfectly sharp photos. Checking hundreds or even thousands of photos for pixel level sharpness is no fun at all, so we made a utility called Pixelpeeper that turns this task from "mind numbingly boring" to "slightly annoying".

The program displays magnified crops for each image. You can quickly inspect, select and move images that are not up to quality (for example images with camera shake or misfocus). Multiple cropping modes are available, to show crops of both the center and corners of the image.

Pixelpeeper loads images in both 8-bit and 16-bit, and supports the following file formats:

  • JPEG
  • TIFF
  • PNG
  • PSD (files saved with compatibility mode only)
We found it to be a huge timesaver, so we decided to have it rewritten and release it as a free utility for the (always helpful) Photoscan community.

Pixelpeeper Download (0.99MB)

Windows 7 64-bit or higher required, more than 4GB of memory recommended. No installer needed, the program is a single executable that can be placed anywhere. Use at your own risk, please do not redistribute or re-upload.

Questions or ideas can be posted in this thread or emailed to

Feature Requests / "Show/Hide Cameras" shortcut key
« on: March 27, 2015, 03:24:20 PM »
I use Show/Hide Cameras a lot, because often the cameras obstruct the scan/region.

It would be really nice if there was a shortcut key for this (for example SHIFT-5 to toggle).

General / Alignment Experiments
« on: March 14, 2015, 12:35:43 PM »
I did some tests to find out what the the influence of the Key Point Limit is on the alignment because it always bugged me not knowing what what Key Point Limit was high enough.

This is the project I used for testing, a scan of an rusty sewer lid:

It's photographed with a D800 and a 35mm lens, and has a total of 52 photos at 36MP resolution.

I ran alignments with the following settings:

Accuracy: High
Pair pre-selection: Generic
Key point limit: from 1000 all the way up to 320000
Tie point limit: 0 (no limit)

Quick explanation of the settings:

At High accuracy, Photoscan uses the full resolution photo  (Medium would use the image at 50%, Low at 25%).

Pair Pre Selection
With Pair pre-selection set to Generic, Photoscan will make a quick pre-scan to see which photos share the same view. If photos do not share the same view then it makes no sense to compare the points in the photos. This makes the alignment much faster (and with good quality photos it has no impact on quality at all)

Key Point Limit
The maximum number of points Photoscan will extract from each photo. For a high quality 36 Megapixel photo the maximum number of points that can be extract is usually around 240000. For a 21 Megapixel photo this is generally 180000 points.

Tie Point Limit
This setting has been added not so long ago. I am not completely sure, but I think when this setting is active Photoscan makes a pre-selection based on (visual) quality of the extract points (so it only compares the highest quality points).

For example, if your Key Point limit is set to 40000 and the Tie Point Limit is set to 1000, then Photoscan will first extract 40000 points for each photo, and only keep the best 1000 points. These 1000 points per photo are then used for the alignment calculations.

This would speed up the alignment a lot because there is only a fraction of the points to compare, but since I am not sure about this setting I have set this value to 0 (=no maximum).

I ran alignments for Key point limits from 1000 all the way up to 320000, and put the results in some graphs.

Number of Points in the Sparse Cloud after alignment:

A higher Key point limit means more points in the Sparse Cloud. It starts levelling off after 240.000 points, because the maximum number of points that can be extracted is being reached for some images.

Alignment time:

The alignment time is pretty much linear, which was a surprise to me because I expected it to be exponential. The graph varies a bit, because I was using my computer for other things as well so the times are not completely accurate.

Reprojection Error

The next graph is the reprojection error:

The Reprojection error is a measure of accuracy of the points, measured in pixels. When you think about this, these values are pretty impressive: Photoscan is able to align the cameras with a sub-pixel accuracy!

The reprojection error for an alignment with 40.000 points is almost twice as big as for an alignment with 120.000 points (0.7 vs 0.4 pixels). But we can optimize the Sparse Point Cloud and redo the camera alignment.

To do this, I have used Edit->Gradual Selection->Reprojection Error with a value of 0.5 and removed those points. This gets rid of all points with a reprojection error larger than 0.5 (about a third of the points in the Sparse Cloud) Then I used Tools->Optimize Cameras to redo the alignment of the cameras. After optimizing, the graph for the reprojection error looks like this.

So after optimization the reprojection error is pretty much the same for all Key point limits (and I did not loose that many points) . The reprojection error now has values around 0.25, so Photoscan managed to align the cameras with a precision a quarter of a pixel!

I tried optimizing the point cloud even further by using "Gradual Selection -> Reconstruction Uncertainty = 8", but the reprojection error actually increased slightly after these optimizations. I don't think the accuracy is actually worse (since I deleted bad points), so maybe the reprojection error is not the best indicator of the accuracy of the alignment?

Dense Cloud Quality

All this talk about Reprojection Error is pretty theoretical, what is the effect on the Dense Point Cloud?
I did a Dense Cloud reconstruction at "High" quality for the various alignments. I converted the result to a normalmap, because we know from experience that a normalmap shows problems really well.

10000 points: there are some cameras that are excluded from the Dense Cloud reconstruction, so the Dense Cloud has some holes. Also, there is some general noise all over the scan.

20000 points: looks much better, but there is a very slight noise (only visible if you overlay the normalmaps).

40000 points: scan looks good

more than 40000 points: no visible difference in quality.

I also did a comparison with the Dense Cloud build at the Ultra quality setting. There wasn't any visible difference either.


The default value for the Key point limit (40000 points) seems to be well chosen. I don't see any improvement in quality of the Dense Cloud when using an alignment with more than 40000 Key points. If you look at the values of the reprojection error after optimization, this actually makes sense. The values are all under 0.3 pixels, which is well under the size of the details in the Dense Cloud. The alignment might be 0.1 pixel more precise, but this is way below the threshold of visibility (I would estimate that details in the Dense Cloud are for structures at least 2-3 pixels in size).

I will probably run my alignments at a higher Key point limit anyway (maybe 120000 points), just to be sure that my alignment is as accurate as possible. The Alignment doesn't take that much time compared to the DC reconstruction, and it gives me that warm safe feeling of doing it right.  :)

Please note that your results may vary: this is a very specific type of scan where all the photos are in the same plane. A more 3D object might need more points for a good alignment. Also, the photos in this project have almost perfect sharpness, so Photoscan has a very good input. If the photos would be less sharp, more points would be deleted during optimization (and using more points might be useful).


I would really like support for Transparancy for the TIFF file format, or support for PSD files (without layers), so that I can do my masking in Photoshop.

I can mask much faster in Photoshop, so it would be a huge timesaver to be able to erase unwanted regions this way.

General / Alignment algorithm, does color matter?
« on: July 06, 2014, 10:23:58 PM »
I am trying to scan an interior which has white plastered walls. The walls are too featureless to align well, so I'm thinking of adding some small pieces of painters tape on the wall (ripped into random shapes) to give Photoscan better features to extract.

My question is if the point matching is color sensitive, or if it operates on black and white. If it is color sensitive I can use several different colors tape for even more differentiation. (Even better would be a roll of tape printed with random shapes!)

Bug Reports / Forum search bug
« on: July 02, 2014, 07:32:35 AM »
The forum search function does not sort by date somehow. For example, when I search for "Arbitrary" the first result is from May 18, 2014, and the fourth result is from June 23.

This makes it a bit hard to find posts, because I would need to go through all pages. Perhaps this is a setting in the forum software that can easily be changed?

A lot of users are asking for help with problems in their scans, without showing their source photos. To me this is a bit like saying "I made this drawing and it doesn't look good,  please help me"  ... without showing the actual drawing.

If we can't see your source photos, often we can only make an educated guess to the cause of your problem. With an example of a source photo we can see much more easily what is causing the problem, and how you can improve your results.

So if you are having problems in Photoscan please upload at least a single source photo at full resolution.

Feature Requests / Photoscan Professional "Artist" Edition
« on: April 16, 2014, 10:20:20 PM »
In one of the threads in the general forum we discussed a Professional "Artist" Edition of Photoscan. I want to put it here to see if more users agree.

A lot of us artists would love to use the phyton scripting and "Optimize Alignment" tools in the Professional edition, but we cannot justify the 3400$ pricetag for just these 2 features.

I think a lot of artists would be more than happy to pay (for example) 750$ for a version of Photoscan Professional that is stripped of all the aerial photography features that we never need (DEMs, Georeferencing, Multispectral imagery processing, etc).

General / Single camera scanning thread?
« on: April 14, 2014, 11:10:30 AM »
What happened to it? Suddenly it's gone, or have I been dreaming?

Feature Requests / Shortcut key for "Show Cameras"
« on: March 21, 2014, 04:27:10 PM »
I use the "show/hide cameras" function a lot, a keyboard shortcut for this function would be really nice!

Bug Reports / Gradual Selection
« on: March 20, 2014, 11:07:39 AM »
Gradual selection is very slow on projects with a larger sparse cloud (for example, 12 million points).

1) It would be great if the selection only updated after I let go of the slider. Currently it tries to update the selection realtime, which means Photoscan hangs for seconds at a time when I try to move the slider.

2) The "Image Count" slider starts at Max images. It would be more logical to have it start at Min images (the value of "2"). I assume most people want to use this function to delete points with only 2 images (the less accurate points).

These are not really bugs, but it would make removing less accurate points from the sparse cloud much faster.

Edit: allowing keyboard input in the number field would also be useful!

Bug Reports / Estimate Image Quality - inconsistent results
« on: January 17, 2014, 01:50:37 PM »
We are struggling with picking out photos with motion blur using the Estimate Image Quality function. Sometimes images with higher than average estimated image quality are blurred anyway. At other times, images with low estimated quality are actually pretty sharp.

I did some tests with an artificial noise pattern, and the results are a bit inconsistent. When I add more blur to a noise pattern, the estimated quality actually goes up. The sharpest version has a lower estimated images quality than a version with a large amount of blur. Please see attached image with crops of the noise patterns and Image Quality values.

It would be great if the Estimate Image Quality fucntion would reliably pick out blurred images, because having to go through a sets of 400+ photos manually is no fun :)


General / How many photos does Agisoft use to create a point
« on: December 21, 2013, 01:56:30 PM »
In the interest of understanding the whole process I was wondering: how many photos does Agisoft use to create a point in the Dense Cloud?

Does it reconstruct points from just 2 photos like Agisoft Stereoscan? So does it work with photo pairs only, or does it reconstruct depth using 3 or more photos?

Feature Requests / Request: Dense Cloud Filtering
« on: December 14, 2013, 10:53:14 PM »
We are struggling with building the mesh for projects with very big Dense Clouds (200 million points or more).

The problem is that the Build Mesh stage always builds the mesh using the entire point cloud. So even if we build a mesh with a 80 million polygon target, it will first build the mesh with the maximum amount of polygons (using all points in the cloud), and only decimate afterwards. This takes a lot of time and we often run out of memory, even with 128GB.

What would be a very good solution, is if we could optimize/decimate the Dense Cloud. For example, in MeshLab you can use "Poisson Disk Sampling", this function filters the point cloud and removes (unnecessary) points.

We would love to have such a function in Photoscan. This would save us a lot of time, and depending on the filtering algorithm it could result in a mesh that is the same quality as the unfiltered Dense Cloud.

General / How bandwidth intensive (PCIe) is Photoscan?
« on: November 19, 2013, 08:57:03 PM »
How bandwidth intensive is Photoscan? Bitcoin miners aren't very bandwidth intensive for example, you can plug a graphics card in a PCI 1x slot and the performance would be similar to a card in a PCI 16x slot (because the card spends most it's time crunching numbers, and doesn't send/receive much data).

Is this the same with Photoscan? Could I use an extra graphics card in a PCI 1x slot, or would this card have low performance?

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