External features extraction

theia_opencv

/* Reimplementation of `AddImagesToReconstructionBuilder`
   https://github.com/sweeneychris/TheiaSfM/blob/master/applications/build_reconstruction.cc#L334
   Using an external local features extractor. In this case AKAZE from OpenCV.
*/
void AddImagesToReconstructionBuilder(
    ReconstructionBuilder* reconstruction_builder) {
  std::vector<std::string> image_files;
  CHECK(theia::GetFilepathsFromWildcard(FLAGS_images, &image_files));

  // Create the feature matcher.
  theia::FeatureMatcherOptions matching_options;
  theia::VerifyTwoViewMatchesOptions verification_options;
  SetMatchingOptions(&matching_options, &verification_options);
  const theia::MatchingStrategy matching_strategy =
      StringToMatchingStrategyType(FLAGS_matching_strategy);
  std::unique_ptr<theia::FeatureMatcher<theia::L2> > matcher =
      CreateFeatureMatcher(matching_strategy, matching_options);

  cv::Mat img, opencv_descs;
  std::vector<cv::KeyPoint> opencv_kpts;
  cv::Ptr<cv::Feature2D> extractor = cv::AKAZE::create();

  std::vector<theia::Keypoint> theia_kpts;
  std::vector<Eigen::VectorXf> theia_descs;

  for (size_t i = 0; i < image_files.size(); ++i) {
    img = cv::imread(image_files[i], cv::IMREAD_COLOR);
    extractor->detectAndCompute(img, cv::Mat(), opencv_kpts, opencv_descs);

    // conversion between OpenCV/Theia
    opencv_kpts_to_theia(opencv_kpts, &theia_kpts);
    opencv_descriptors_to_theia(opencv_descs, &theia_descs);

    std::string image_name;
    theia::GetFilenameFromFilepath(image_files[i], true, &image_name);

    matcher->AddImage(image_name, theia_kpts, theia_descs);
    LOG(INFO) << "Added Image " << image_name << " with "
              << theia_kpts.size() << " Keypoints, "
              << theia_descs.size() << " Descriptors";
  }

  LOG(INFO) << "Perform MATCHING!";

  std::vector<theia::ImagePairMatch> image_matches;
  //matcher->MatchImages(&image_matches);

  // Or, with geometric verification:
  matcher->MatchImagesWithGeometricVerification(
    verification_options, &image_matches);

  // Optionally read the intrinsics from a calibration file.
  std::vector<theia::CameraIntrinsicsPrior> camera_intrinsics_prior;
  ReadIntrinsicsFromCalibrationFile(image_files, &camera_intrinsics_prior);

  // Write the matches out.
  LOG(INFO) << "Writing matches to file: " << FLAGS_output_matches_file;
  CHECK(theia::WriteMatchesAndGeometry(FLAGS_output_matches_file,
                                       image_files,
                                       camera_intrinsics_prior, image_matches))
      << "Could not write the matches to " << FLAGS_output_matches_file;

  // Add all the views.
  for (int i = 0; i < image_files.size(); i++) {
    reconstruction_builder->AddImage(image_files[i]);
  }

  // Add the matches.
  for (const auto& match : image_matches) {
    CHECK(reconstruction_builder->AddTwoViewMatch(match.image1,
                                                  match.image2,
                                                  match));
  }
}

Hi,

It seems like you have not built ceres with suite sparse. The problem is not with feature detector , it's the bundle adjustment which is failing. You could give linear solver as DENSE_SCHUR. Or build ceres with one of the sparse libraries such as Suitesparse , CXSparse or Eigen Sparse.

Correction:

Ignore the bundle adjustment part. Just build ceres with sparse library. It's the position estimator , where ceres is asking for suitesparse.

@avanindra is correct. You should build Ceres with SuiteSparse (the failing module is for position estimation) then this problem will be fixed.

Suitesparse was detected during Ceres installation. Just tried to reinstall everything again to be sure but got the same log. I'm using the Global solver which fails, however with Incremental got an approximated result of the real solution.

edgarriba,

Would you mind to share your code for the following functions?
opencv_kpts_to_theia(opencv_kpts, &theia_kpts);
opencv_descriptors_to_theia(opencv_descs, &theia_descs);
I need to use these functions but don't want to reinvent the wheels.... Thank you!