openMVG_main_SfM --sfm_engine "GLOBAL"

[GlobalACSfM]_ is based on the paper "Global Fusion of Relative Motions for Robust, Accurate and Scalable Structure from Motion." published at ICCV 2013.

Multi-view structure from motion (SfM) estimates the position and orientation of pictures in a common 3D coordinate frame. When views are treated incrementally, this external calibration can be subject to drift, contrary to global methods that distribute residual errors evenly. Here the method propose a new global calibration approach based on the fusion of relative motions between image pairs.

Algorithm of the Global Structure from Motion

.. code-block:: c++

Require: internal camera calibration (possibly from EXIF data) Require: pairwise geometry consistent point correspondences Ensure: 3D point cloud Ensure: camera poses

compute relative pairwise rotations detect and remove false relative pairwise rotations - using composition error of triplet of relative rotations compute the global rotation - using a dense least square and approximated rotations compute relative translations - using triplet of views for stability and colinear motion support compute the global translation - integration of the relative translation directions using a l-∞ method. final structure and motion - link tracks validated per triplets and compute global structure by triangulation, - refine estimated parameter in a 2 step Bundle Adjustment - refine structure and translations - refine structure and camera parameters (rotations, translations).

Information and usage

The chain is designed to run on a sfm_data.json file and some pre-computed matches. The chain will only consider images with known approximate focal length. Image with invalid intrinsic id will be ignored.

.. code-block:: c++

$ openMVG_main_SfM --engine GLOBAL -i Dataset/matches/sfm_data.json -m Dataset/matches/ -o Dataset/out_Global_Reconstruction/

Arguments description:

Required parameters:

• [-i|--input_file]

  • a SfM_Data file

• [-m|--matchdir]

  • path were geometric matches were stored

• [-o|--outdir]

  • path where the output data will be stored

Optional parameters:

• [-r|--rotationAveraging]

  • 1: L1 rotation averaging _[Chatterjee]
  • 2: (default) L2 rotation averaging _[Martinec]

• [-t|--translationAveraging]

  • 1: (default) L1 translation averaging _[GlobalACSfM]
  • 2: L2 translation averaging _[Kyle2014]
  • 3: (default) SoftL1 minimization _[GlobalACSfM]

• [-f|--refineIntrinsics] User can control exactly which parameter will be considered as constant/variable and combine them by using the '|' operator.

  • ADJUST_ALL -> refine all existing parameters (default)

  • NONE -> intrinsic parameters are held as constant

  • ADJUST_FOCAL_LENGTH -> refine only the focal length

  • ADJUST_PRINCIPAL_POINT -> refine only the principal point position

  • ADJUST_DISTORTION -> refine only the distortion coefficient(s) (if any)

  • NOTE Options can be combined thanks to '|':

    • ADJUST_FOCAL_LENGTH|ADJUST_PRINCIPAL_POINT -> refine the focal length & the principal point position

    • ADJUST_FOCAL_LENGTH|ADJUST_DISTORTION -> refine the focal length & the distortion coefficient(s) (if any)

    • ADJUST_PRINCIPAL_POINT|ADJUST_DISTORTION -> refine the principal point position & the distortion coefficient(s) (if any)

_[GlobalACSfM] default settings are "-r 2 -t 3".

Tips

As a dense image network is required to perform global SfM it is required to detect more Regions points per image to ensure a high probability of matching.

Please use:

• "-p HIGH" option on openMVG_main_ComputeFeatures
• "-r .8" on openMVG_main_ComputeMatches.