I’m experimenting with mapping the seafloor for restoration projects. This is what I have done so far:
- Record a time-lapse sequence, swim as slow as possible (GoPro Hero 7 Black linear 0.5sec)
- Buy ArgiSoft Metashape Standard (about $300NZD)
- Import photos to chunk
- Align photos (Duplication errors on highest, high best, Reference preselection [sequential], Guided image matching)
- Don’t clean up the point cloud (not needed for orthomosaics)
- Build mesh (use sparse cloud source data, Arbitrary 3D)
- Build texture (Adaptive orthophoto, Mosaic, Enable hole filling, Enable ghosting filter)
- Capture view (hide cameras and other visual aids first then export .PNG at a ridiculous resolution)
ArgiSoft Metashape worked much better than using Adobes photo stitching software (Photoshop & Lightroom) on the same data. But I need more overlapping images as all the software packages were not able to match all of any of the four test sequences I did.
I’m going to test shooting in video next. The frames will be smaller 2704×1520 (if I stick with linear to avoid extra processing for lens distortion) instead of 4000×3000 with the time-lapse but I’m hopping all the extra frames will more than compensate (2FPS=>24FPS).
In theory an ROV will be better but I don’t think there are any on the market that know where they are based on what they can see. All the work arounds for knowing where you are underwater are expensive, here are two UWIS & Nimrod. I want to see if we can do this with divers and no location data. I don’t think towing a GPS will be accurate enough to match up the photos but it does seem to work with drones taking images of bigger scenes (I want this to work in 50cm visibility). I expect if I want large complete images the diver will need to follow another diver who has left a line on the seafloor. One advantage of this is that the line could have a scale on it, but I’m hoping to avoid it as the lines will be ugly 😀 So far I can do only two turns before it fails. There are three patterns that might work (Space invaders, Spirals and Pick up sticks). For my initial trials I am focusing on Space invaders.
Video provides lots more frames and the conversion is easy. A land based test with GPS disabled, multiple turns, 2500 photos, 2704 x 2028 linear, space invader pattern at 1.2m from the ground worked perfectly. However I cant get it to work underwater. In every test so far Metashape will only align 50-100 frames. I tried shooting on a sunny day which was terrible as the reflection of the waves dancing on the seafloor confuses the software. But two follow up shoots also failed, when I look at the frames Metashape cant match I just don’t see why its can’t align them. Theses two images are in sequence, one gets aligned and the next one is dropped!
Here is what the test footage looks like, I have increased the contrast.
I have also tried exporting the frames at 8fps to see if the alignment errors are happening because the images are too similar but got similar results (faster).
Detailed advice from Metashape:
Since you are using Sequential pre-selection, you wouldn’t get matching points for the images from the different lines of “space invader” or “pick up sticks” scenarios or from different radius of “spiral” scenario.
If you are using “space invader” scenario and have hundreds or thousands of images, it may be reasonable to align the data in two iterations: with sequential preselection and then with estimated preselection, providing that most of the cameras are properly aligned.
As for the mesh reconstruction – using Sparse Cloud source would give you very rough model, so you may consider building the model from the depth maps with medium/high quality in Arbitrary mode. As for the texture reconstruction, I can suggest to generate it in Generic mode and then in the model view switch the view from Perspective to Orthographic, then orient the viewpoint in the desired way and use Capture View option get a kind of planar orthomosaic projection for your model.
Align ‘sequential’ only ever gets about 5% of the shots. Repeating the alignment procedure on ‘estimated’ picks up the rest but the camera alignment gets curved. I think I have calibrated the cameras to 24mm (it’s hard to see if that has been applied) but it doesn’t seem to change things.
I tried an above water test and made a two minute video of the Māori fish dams at Tahuna Torea. I used the same settings as above, but dropped the quality down to medium. It looks great!
The differences between above and below water are: Camera distance to subject, flotsam, visibility / image quality and colour range. If the footage I am gathering is too poor for Metashape to align it might mean we need less suspended sediment in the water to make the images. That’s a problem as the places I want to map are suffering from suspended sediment – which is why they would benefit from shellfish restoration.
The Agisoft support team are awesome. They processed my footage with f = 1906 in the camera calibration, align photos without using preselection and a 10,00 tie point limit. The alignment took 2.5 days but worked perfectly (click on the image below). There are a few glitches but I think the result is good enough for mapping life on the seafloor. I will refine the numbers a bit and post them in a seperate blog post, wahoo!