bsfm::FundamentalMatrixRansacProblem Class Reference

#include <fundamental_matrix_ransac_problem.h>

Inheritance diagram for bsfm::FundamentalMatrixRansacProblem:

Public Member Functions
	FundamentalMatrixRansacProblem ()
virtual	~FundamentalMatrixRansacProblem ()
virtual std::vector< FeatureMatch >	SampleData (unsigned int num_samples)
virtual std::vector< FeatureMatch >	RemainingData (unsigned int num_sampled_previously) const
virtual FundamentalMatrixRansacModel	FitModel (const std::vector< FeatureMatch > &input_data) const
Public Member Functions inherited from bsfm::RansacProblem< FeatureMatch, FundamentalMatrixRansacModel >
	RansacProblem ()
virtual	~RansacProblem ()
virtual void	SetModel (const FundamentalMatrixRansacModel &model)
virtual void	SetData (const std::vector< FeatureMatch > &data)
virtual void	SetInliers (const std::vector< FeatureMatch > &inliers)
virtual void	SetSolutionFound (bool solution_found)
virtual bool	SolutionFound ()
virtual const FundamentalMatrixRansacModel &	Model () const
virtual const std::vector< FeatureMatch > &	Inliers () const

Additional Inherited Members
Protected Attributes inherited from bsfm::RansacProblem< FeatureMatch, FundamentalMatrixRansacModel >
std::vector< FeatureMatch >	data_
std::vector< FeatureMatch >	inliers_
FundamentalMatrixRansacModel	model_
bool	solution_found_

Detailed Description

Definition at line 87 of file fundamental_matrix_ransac_problem.h.

Constructor & Destructor Documentation

bsfm::FundamentalMatrixRansacProblem::FundamentalMatrixRansacProblem

(

)

Definition at line 106 of file fundamental_matrix_ransac_problem.cpp.

{}

bsfm::FundamentalMatrixRansacProblem::~FundamentalMatrixRansacProblem ( )

virtual

Definition at line 109 of file fundamental_matrix_ransac_problem.cpp.

{}

Member Function Documentation

FundamentalMatrixRansacModel bsfm::FundamentalMatrixRansacProblem::FitModel ( const std::vector< FeatureMatch > &  input_data ) const

virtual

Implements bsfm::RansacProblem< FeatureMatch, FundamentalMatrixRansacModel >.

Definition at line 147 of file fundamental_matrix_ransac_problem.cpp.

                                                     {
  // Create an empty fundamental matrix.
  Matrix3d F;

  // Run the 8-point algorithm with default options.
  EightPointAlgorithmSolver solver;
  FundamentalMatrixSolverOptions options;
  solver.SetOptions(options);

  if (solver.ComputeFundamentalMatrix(input_data, F)) {
    // Create a new RansacModel using the computed fundamental matrix.
    FundamentalMatrixRansacModel model_out(F);

    // Record sum of squared error over all matches.
    model_out.error_ = 0.0;
    for (const auto& feature_match : input_data) {
      const double error = model_out.EvaluateEpipolarCondition(feature_match);
      model_out.error_ += error * error;
    }

    return model_out;
  }
  // Set a large error - we didn't find a model that fits the data.
  FundamentalMatrixRansacModel model_out(Matrix3d::Identity());
  model_out.error_ = std::numeric_limits<double>::infinity();
  return model_out;
}

std::vector< FeatureMatch > bsfm::FundamentalMatrixRansacProblem::RemainingData ( unsigned int  num_sampled_previously ) const

virtual

Implements bsfm::RansacProblem< FeatureMatch, FundamentalMatrixRansacModel >.

Definition at line 133 of file fundamental_matrix_ransac_problem.cpp.

                                               {
  // In Sample(), the data was shuffled and we took the first
  // 'num_sampled_previously' elements. Here, take the remaining elements.
  if (num_sampled_previously >= data_.size()) {
    VLOG(1) << "No remaining RANSAC data to sample.";
    return std::vector<FeatureMatch>();
  }

  return std::vector<FeatureMatch>(
      data_.begin() + num_sampled_previously, data_.end());
}

std::vector< FeatureMatch > bsfm::FundamentalMatrixRansacProblem::SampleData ( unsigned int  num_samples )

virtual

Implements bsfm::RansacProblem< FeatureMatch, FundamentalMatrixRansacModel >.

Definition at line 112 of file fundamental_matrix_ransac_problem.cpp.

                              {
  // Randomly shuffle the entire dataset and take the first elements.
  std::random_shuffle(data_.begin(), data_.end());

  // Make sure we don't over step.

  if (static_cast<size_t>(num_samples) > data_.size()) {
    VLOG(1) << "Requested more RANSAC data samples than are available. "
               "Returning all data.";
    num_samples = data_.size();
  }

  // Get samples.
  std::vector<FeatureMatch> samples(
      data_.begin(), data_.begin() + static_cast<size_t>(num_samples));

  return samples;
}

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The documentation for this class was generated from the following files:

• /Users/eanelson/Git/berkeley_sfm/src/cpp/ransac/fundamental_matrix_ransac_problem.h
• /Users/eanelson/Git/berkeley_sfm/src/cpp/ransac/fundamental_matrix_ransac_problem.cpp