openMVG_main_ComputeMatches¶
This binary compute images that have a visual overlap. Using image descriptions computed by openMVG_main_ComputeFeatures, we establish the corresponding putative photometric matches and filter the resulting correspondences using some robust geometric filters.
$ openMVG_main_ComputeMatches -i [..\matches\sfm_data.json] -o [...\matches]
Arguments description:
Required parameters:
[-i|–input_file]
a SfM_Data file
[-o|–out_dir path]
path were putative and geometric matches will be stored
Optional parameters:
[-f|–force: Force to recompute data]
0: (default) reload previously computed data (useful when you have kill the process and want to continue to compute)
1: useful when you change have changed a command line parameter, force recomputing and re-saving.
[-r|-ratio]
(Nearest Neighbor distance ratio, default value is set to 0.6). 0.8 is less restrictive and advised.
[-g|-geometric_model]
type of model used for robust estimation from the photometric putative matches
f: Fundamental matrix filtering
e: Essential matrix filtering (all the image must have the same known focal length)
h: Homography matrix filtering
[-n|–nearest_matching_method]
AUTO: auto choice from regions type,
BRUTEFORCEL2: BruteForce L2 matching for Scalar based regions descriptor,
BRUTEFORCEHAMMING: BruteForce Hamming matching for binary based regions descriptor,
ANNL2: Approximate Nearest Neighbor L2 matching for Scalar based regions descriptor.
[-v|–video_mode_matching]
(sequence matching with an overlap of X images)
X: with match 0 with (1->X), …]
2: will match 0 with (1,2), 1 with (2,3), …
3: will match 0 with (1,2,3), 1 with (2,3,4), …]
[-l|–pair_list]
file that explicitly list the View pair that must be compared
Once matches have been computed you can, at your choice, you can display detected, matches as SVG files:
Detected keypoints: openMVG_main_exportKeypoints
Putative, Geometric matches: openMVG_main_exportMatches
Tracks: openMVG_main_exportTracks
Or start the 3D reconstruction: