openMVG samples

openMVG focus on a strong implementation checking of the provided features. To do so it provides unit test (that assert code results and helps user to see how the code must be used) but it provides also illustrated samples of the major features.

The samples can be seen as showcase and tutorials:

imageData

  • some pictures for each of the following examples.

features_siftPutativeMatches

Show how:
  • extract SIFT features and descriptors,
  • match features descriptors,
  • display the computed matches.

features_affine_demo

Show how:
  • use the MSER/TBMR region detector
  • display regions fitted ellipses

features_image_matching

Show how:
  • use the Image_describer interface to extract features & descriptors
  • match the detected regions
  • display detected features & corresponding matches

features_kvld_filter

Show how:
  • filter putative matches with the K-VLD filter [KVLD12].

features_repeatability

Show how to use Oxford’s “Affine Covariant Regions Datasets” image datasets in order to compute feature position and or descriptor matching repeatability measures.

multiview_robust_homography

Show how:
  • estimate a robust homography between features matches.

multiview_robust_homography_guided

Show how:
  • estimate a robust homography between features matches,
  • extend the putative matches with a H guided filter,
  • warp the query image over the reference image.

multiview_robust_fundamental

Show how:
  • estimate a robust fundamental matrix between features matches.

multiview_robust_fundamental_guided

Show how:
  • estimate a robust fundamental matrix between features matches,
  • extend the putative matches with a F guided filter.

multiview_robust_essential

Show how:
  • estimate a robust essential matrix between features matches,
  • compute the 3D structure by triangulation of the corresponding inliers.

multiview_robust_essential_ba

Show how:
  • refine with bundle_adjustment the Structure and Motion of a scene
  • for different camera model:
    • Refine [X],[f,R|t] (individual cameras),
    • Refine [X],[R|t], shared [f],
    • Refine [X],[R|t], shared brown disto models.

multiview_robust_essential_spherical

Show how:
  • estimate a robust essential matrix between two spherical panorama
  • triangulate remaning inliers.

exif_Parsing

Show how:
  • parse JPEG EXIF metadata

exif_sensorWidthDatabase

Show how:
  • use the camera sensor width database

cameras_undisto_Brown

Show how:
  • undistord a picture according known Brown radial parameters.

openMVG_sample_pano_converter

Show how extract many rectilinear images from a spherical panorama.

Don’t hesitate to help to extend the list.