OpenGV
A library for solving calibrated central and non-central geometric vision problems
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File List
Here is a list of all documented files with brief descriptions:
[detail level 12345]
 
include
 
opengv
 
absolute_pose
 
AbsoluteAdapterBase.hpp
Adapter-class for passing bearing-vector-to-point correspondences to the absolute-pose algorithms
 
AbsoluteMultiAdapterBase.hpp
Adapter-class for passing bearing-vector-to-point correspondences to the absolute-pose algorithms. Intended for absolute non-central- viewpoint problems. Access of correspondences etc. via an additional frame-index referring to the camera
 
CentralAbsoluteAdapter.hpp
Adapter-class for passing bearing-vector-to-point correspondences to the central absolute-pose algorithms. It maps opengv types back to opengv types
 
MACentralAbsolute.hpp
Adapter-class for passing bearing-vector-to-point correspondences to the central absolute-pose algorithms. It maps matlab types back to opengv types
 
MANoncentralAbsolute.hpp
Adapter-class for passing bearing-vector-to-point correspondences to the non-central absolute-pose algorithms. It maps matlab types to opengv types
 
methods.hpp
Methods for computing the absolute pose of a calibrated viewpoint
 
NoncentralAbsoluteAdapter.hpp
Adapter-class for passing bearing-vector-to-point correspondences to the non-central absolute-pose algorithms. It maps opengv types back to opengv types
 
NoncentralAbsoluteMultiAdapter.hpp
Adapter-class for passing bearing-vector-to-point correspondences to the non-central absolute-pose algorithms. It maps opengv types back to opengv types. Manages multiple match-lists for each camera. This allows to draw samples homogeneously over the cameras
 
math
 
arun.hpp
Arun's method for computing the rotation between two point sets
 
cayley.hpp
Functions for back-and-forth transformation between rotation matrices and Cayley-parameters
 
gauss_jordan.hpp
Sparse, fast Gauss Jordan elimination
 
quaternion.hpp
Functions for back-and-forth transformation between rotation matrices and quaternion-parameters
 
roots.hpp
Closed-form solutions for computing the roots of a polynomial
 
Sturm.hpp
Class for evaluating Sturm chains on polynomials, and bracketing the real roots
 
point_cloud
 
MAPointCloud.hpp
Adapter-class for passing 3D point correspondences. Maps matlab types to opengv types
 
methods.hpp
Methods for computing the transformation between two frames that contain point-clouds
 
PointCloudAdapter.hpp
Adapter-class for passing 3D point correspondences. Maps opengv types back to opengv types
 
PointCloudAdapterBase.hpp
 
relative_pose
 
CentralRelativeAdapter.hpp
Adapter-class for passing bearing-vector correspondences to the central relative-pose algorithms. Maps opengv types back to opengv types
 
CentralRelativeMultiAdapter.hpp
Adapter-class for passing bearing-vector correspondences to the central relative-pose algorithms. Maps opengv types back to opengv types. For multi-central-viewpoint. Manages multiple match-lists for pairs of cameras (e.g. pairs of central viewpoints)
 
CentralRelativeWeightingAdapter.hpp
Adapter-class for passing bearing-vector correspondences to the central relative-pose algorithms. Maps opengv types back to opengv types. Also contains "weights" reflecting the quality of a feature correspondence (typically between 0 and 1)
 
MACentralRelative.hpp
Adapter-class for passing bearing-vector correspondences to the central relative-pose algorithms. Maps matlab types to opengv types
 
MANoncentralRelative.hpp
Adapter-class for passing bearing-vector correspondences to the non-central relative-pose algorithms. Maps matlab types to opengv types
 
MANoncentralRelativeMulti.hpp
Adapter-class for passing bearing-vector correspondences to the non-central relative-pose algorithms. Maps Matlab types to opengv types. Manages multiple match-lists for pairs of cameras. This allows to draw samples homogeneously over the cameras
 
methods.hpp
A collection of methods for computing the relative pose between two calibrated central or non-central viewpoints
 
NoncentralRelativeAdapter.hpp
Adapter-class for passing bearing-vector correspondences to the non-central relative-pose algorithms. Maps opengv types back to opengv types
 
NoncentralRelativeMultiAdapter.hpp
Adapter-class for passing bearing-vector correspondences to the non-central relative-pose algorithms. Maps opengv types back to opengv types. Manages multiple match-lists for pairs of cameras. This allows to draw samples homogeneously over the cameras
 
RelativeAdapterBase.hpp
Adapter-class for passing bearing-vector correspondences to the relative-pose algorithms
 
RelativeMultiAdapterBase.hpp
Adapter-class for passing bearing-vector correspondences to the relative-pose algorithms. Intended for multi-central-viewpoint or relative non-central-viewpoint problems. Access of correspondences etc. via an additional pair-index referring to the pairs of cameras
 
sac
 
Lmeds.hpp
Implementation of the Lmeds algorithm
 
MultiRansac.hpp
Implementation of the Ransac algorithm as outlined in [15]. This version is intended for use with the RelativeMultiAdapterBase, and attempts to do sampling in multiple camera-pairs in each hypothesis instantiation
 
MultiSampleConsensus.hpp
This is a base class for sample consensus methods such as Ransac. Derivatives call the three basic functions of a sample-consensus problem (sample drawing, computation of a hypothesis, and verification of a hypothesis). This version is intended for use with the RelativeMultiAdapterBase, and attempts to do sampling in multiple camera-pairs in each hypothesis instantiation
 
MultiSampleConsensusProblem.hpp
Basis-class for Sample-consensus problems. Contains declarations for the three basic functions of a sample-consensus problem (sample drawing, computation of a hypothesis, and verification of a hypothesis). This version is intended for use with the RelativeMultiAdapterBase, and attempts to do sampling in multiple camera-pairs in each hypothesis instantiation
 
Ransac.hpp
Implementation of the Ransac algorithm as outlined in [15]
 
SampleConsensus.hpp
This is a base class for sample consensus methods such as Ransac. Derivatives call the three basic functions of a sample-consensus problem (sample drawing, computation of a hypothesis, and verification of a hypothesis)
 
SampleConsensusProblem.hpp
Basis-class for Sample-consensus problems. Contains declarations for the three basic functions of a sample-consensus problem (sample drawing, computation of a hypothesis, and verification of a hypothesis)
 
sac_problems
 
absolute_pose
 
AbsolutePoseSacProblem.hpp
Functions for fitting an absolute-pose model to a set of bearing-vector-point correspondences, using different algorithms (central and non-central one). Used in a sample-consenus paradigm for rejecting outlier correspondences
 
MultiNoncentralAbsolutePoseSacProblem.hpp
Functions for fitting an absolute-pose model to a set of bearing-vector-point correspondences, using different algorithms (central and non-central one). Used in a sample-consenus paradigm for rejecting outlier correspondences, which does homogeneous sampling
 
point_cloud
 
PointCloudSacProblem.hpp
Functions for fitting a transformation model between two frames containing point-clouds. Used in a random sample paradigm for rejecting outliers in the correspondences
 
relative_pose
 
CentralRelativePoseSacProblem.hpp
Functions for fitting a relative-pose model to a set of bearing-vector correspondences, using different algorithms (central). Used with a random sample paradigm for rejecting outlier correspondences
 
EigensolverSacProblem.hpp
Functions for fitting a relative-pose model to a set of bearing-vector correspondences, using the eigensolver algorithm. Used with a random sample paradigm for rejecting outlier correspondences
 
MultiCentralRelativePoseSacProblem.hpp
Functions for fitting a multi relative-pose model to sets of bearing-vector correspondences between multiple viewpoints. Exploits mutual agreement. Used within a multi random-sample paradigm for rejecting outlier correspondences. Experimental!
 
MultiNoncentralRelativePoseSacProblem.hpp
Functions for fitting a relative-pose model to a set of bearing-vector correspondences from a multi-camera system (non-central). Uses RelativeMultiAdapterBase for managing correspondence-lists between individual pairs of views, enabling homogeneous sampling over the views. Used in a random-sample paradigm for rejecting outlier correspondences
 
NoncentralRelativePoseSacProblem.hpp
Functions for fitting a relative-pose model to a set of bearing-vector correspondences from a multi-camera system (non-central). Used with a random-sample paradigm for rejecting outlier-correspondences
 
RotationOnlySacProblem.hpp
Functions for fitting a rotation-only model to a set of bearing-vector correspondences. The viewpoints are assumed to be separated by rotation only. Used within a random-sample paradigm for rejecting outlier correspondences
 
TranslationOnlySacProblem.hpp
Functions for fitting a relative-pose model to a set of bearing-vector correspondences. The viewpoints are assumed to be separated by translation only. Used within a random-sample paradigm for rejecting outlier correspondences
 
triangulation
 
methods.hpp
Some triangulation methods. Not exhaustive
 
Indices.hpp
Generic functor base for use with the Eigen-nonlinear optimization toolbox
 
OptimizationFunctor.hpp
Generic functor base for use with the Eigen-nonlinear optimization toolbox
 
types.hpp
A collection of variables used in geometric vision for the computation of calibrated absolute and relative pose