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 0.8).
      Using 0.6 is more restrictive => provides less false positive.
  • [-g|-geometric_model]
    • type of model used for robust estimation from the photometric putative matches
      • f: Fundamental matrix filtering
      • e: Essential matrix filtering
      • h: Homography matrix filtering
  • [-n|–nearest_matching_method]
    • AUTO: auto choice from regions type,
    • For Scalar based descriptor you can use:
      • BRUTEFORCEL2: BruteForce L2 matching for Scalar based regions descriptor,
      • ANNL2: Approximate Nearest Neighbor L2 matching for Scalar based regions descriptor,
      • CASCADEHASHINGL2: L2 Cascade Hashing matching,
      • FASTCASCADEHASHINGL2: (default).
        L2 Cascade Hashing with precomputed hashed regions, (faster than CASCADEHASHINGL2 but use more memory).
    • For Binary based descriptor you must use:
      • BRUTEFORCEHAMMING: BruteForce Hamming matching for binary 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: