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I am working with stationary, terrestrial time-lapse photos where my intention is to capture real change using an approach similar to MEMI (Blanch et al., 2021). If you don't want to find the paper, I essentially align photos from multiple dates (between which some locations in the scene have changed), and then generate dense clouds using the tie points resulting from the combined alignment, but only the photos from one date at a time. I then compare the dense clouds to detect change between dates.

I would prefer to only use v1.8 as separate camera calibration folders are automatically created, which is really useful. Unfortunately, the dense cloud construction step in 1.8 leads to poor quality (nearly empty in some cases) dense clouds. I feel that this might be related to the updated depth map algorithm that was implemented in v1.7. That being said, I can still use v1.6 and get a dense cloud result that suits my needs (real change is effectively captured).

Does anyone have any insight into why this would be happening? If it is due to the new algorithm not being as tolerant of scene changes between photos, could a feature be implemented to allow the use of the older algorithms when desired? My concern is that if older versions become unusable at some point, my workflow will no longer be achievable.


Feature Requests / More detailed dense cloud construction options
« on: April 17, 2022, 11:44:19 PM »

I get good sparse clouds, but dense clouds have holes / missing sections. This seems to be a relatively common issue and related to number of matches or some other sparse cloud statistic. I want the option to force the dense cloud process to use all of the tie points, and then I can go in and manually filter out areas that I don't think are high enough confidence to use. I'll also note that for my research, the dense cloud results using 1.6.6 are closer to what I want than with 1.7 or 1.8. This is because parts of my scene are moving between photos, so the tiepoint accuracy may be low, but I still want to build the cloud in those locations.


Hi all,

I am currently processing some time-lapse photogrammetry data (images) and have a question on markers. Markers were assigned to targets with known coordinates (using a total station) for the initial set of images. These targets have moved since the initial photos. I am trying to align the old photos and new photos together. When aligning all of the photos, Metashape automatically detects the targets from the initial set of photos and labels them in the new photos. Does this have any weighted effect on my alignment steps?

Any thoughts appreciated! Thanks!

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