This application compute corresponding features and robustly triangulate them according the geometry of the known camera intrinsics & poses.
Algorithm of the application
Require: internal + external camera calibration Require: image description regions (features + descriptors) Ensure: 3D point cloud compute image visibility list all the pair that share common visual content - camera frustum based - or structure visbility (SfM tracks) based list triplets of view from pairs for each triplets compute 3 view tracks if tracks triangulable add correspondences to p link 3 views validated matches (p) as tracks robustly triangulate them
Information and usage¶
The chain is designed to run on a sfm_data.json file and some pre-computed matches. The sfm_data file should contains: - valid view with some defined intrinsics and camera poses, - (optional existing structure).
$ openMVG_main_ComputeStructureFromKnownPoses -i Dataset/out_Reconstruction/sfm_data.json -o Dataset/out_Reconstruction/robustFitting.json
- a SfM_Data file with valid intrinsics and poses and optional structure
- path were image descriptions were stored
- path where the updated scene data will be stored
- path to a matches file (pairs of the match files will be listed and used)
- path to a pairs file (only those pairs will be considered to compute the structure) The pair file is a list of view indexes, one pair on each line
- perform a bundle adjustment on the scene (OFF by default)
- maximal pixels reprojection error that will be considered for triangulations (4.0 by default)