OPK Parser exception with DJI image
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Description
I try to use opensfm to parse images taken by a DJI drone equipped with RTK
To verify the correctness of the parser, I use https://github.com/mapillary/OpenSfM/pull/838#issuecomment-1212630210 mentioned method directly triangulation and obtains the sparse model and camera pose with poor accuracy.
But I found that, as shown in the above visualization, some images are completely wrong in the parsed orientation, while others are correct.
I used incremental reconstruction to obtain GT and tried to find the difference between the two, but I found that it was difficult to find a pattern. Some orientations differed by 180 degrees, and some differed by 90 degrees. How can I solve this problem?
Here is a set of images I used for testing: https://drive.google.com/file/d/15ETwKP3Hn1MgdJDdNs6-4ae5uH33xV9V/view?usp=drive_link
test method:
- Perform an incremental rebuild using opensfm and observe that everything is OK
- run ./bin/opensfm reconstruct --algorithm triangulation data/dji, Camera pose error observed
If the camera pose is wrong, then the pairs selection mechanism based on the opk parsing result is wrong, which is a bug for the system.
Can someone help me find the problem?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Download the linked DJI image set and reproduce the issue with ./bin/opensfm reconstruct --algorithm triangulation data/dji. Compare its camera poses and pair selection with the incremental reconstruction and inspect the OPK parsing path referenced by PR #838. Done means identifying and documenting the cause of the inconsistent 90- or 180-degree orientations, with a verified correction.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100