Poor Quality Point Cloud in SfM with Custom Configuration
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 25/100
- Issue type
- Bug
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- python
- Domain
- computer-vision
Research direction
No source file, test, or entry point is named. Start by reproducing the SfM pipeline with the listed settings and sample images, then inspect the configuration and reconstruction diagnostics. Done means identifying a reproducible cause or documenting validated capture and configuration guidance.
Written by the indexing model from the issue text.
Description
I am experiencing issues with the quality of the point cloud generated by my Sfm pipeline. Despite trying various configuration parameters, the resulting point cloud is not good enough. Below are the details of my setup and the steps I have taken so far.
Configuration:
depthmap_min_consistent_views: 3
hahog_edge_threshold: 30
depthmap_save_debug_files: 'no'
feature_min_frames: 12000
Steps Taken:
Captured several images with a distance of 5 meters between each image.
Added an exif_overrides file to the project.
Experimented with various configuration parameters, but the point cloud quality remains unsatisfactory.
Images and Results:
Questions:
Are there any issues with my current configuration that could be causing poor point cloud quality?
What other configuration parameters should I try to improve the point cloud?
Are there best practices for capturing images or additional preprocessing steps that I should follow?
Additional Information:
Attachments:
Sample images of the point cloud
Thank you for your assistance!
@fabianschenk @YanNoun @paulinus
- Dominant language
- Python
- Stars
- 3.8k
- Forks
- 898
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Getting set up
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