SFM Example that reads (any) BAL dataset

examples/SFMExample_bal.cpp

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+/* ----------------------------------------------------------------------------
+
+ * GTSAM Copyright 2010, Georgia Tech Research Corporation,
+ * Atlanta, Georgia 30332-0415
+ * All Rights Reserved
+ * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
+
+ * See LICENSE for the license information
+
+ * -------------------------------------------------------------------------- */
+
+/**
+ * @file    SFMExample.cpp
+ * @brief   Solve a structure-from-motion problem from a "Bundle Adjustment in the Large" file
+ * @author  Frank Dellaert
+ */
+
+// For an explanation of headers, see SFMExample.cpp
+#include <gtsam/inference/Symbol.h>
+#include <gtsam/nonlinear/NonlinearFactorGraph.h>
+#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
+#include <gtsam/slam/PriorFactor.h>
+#include <gtsam/slam/GeneralSFMFactor.h>
+#include <gtsam/slam/dataset.h> // for loading BAL datasets !
+#include <vector>
+
+using namespace std;
+using namespace gtsam;
+
+// We will be using a projection factor that ties a SFM_Camera to a 3D point.
+// An SFM_Camera is defined in datase.h as a camera with unknown Cal3Bundler calibration
+// and has a total of 9 free parameters
+typedef GeneralSFMFactor<SfM_Camera,Point3> MyFactor;
+
+/* ************************************************************************* */
+int main (int argc, char* argv[]) {
+
+  // default file
+  string filename = findExampleDataFile("dubrovnik-3-7-pre");
+
+  // If an argument is given, try loading a file
+  if (argc>1) filename = string(argv[1]);
+
+  ///< The structure where we will save the SfM data
+  SfM_data mydata;
+  assert(readBAL(filename, mydata));
+
+  // Create a factor graph
+  NonlinearFactorGraph graph;
+
+  // Define the camera observation noise model
+  noiseModel::Isotropic::shared_ptr noise =
+      noiseModel::Isotropic::Sigma(2, 1.0); // one pixel in u and v
+
+  // Add measurements to the factor graph
+  size_t j = 0;
+  BOOST_FOREACH(const SfM_Track& track, mydata.tracks) {
+    BOOST_FOREACH(const SfM_Measurement& measurement, track.measurements) {
+      size_t i; Point2 uv;
+      boost::tie(i, uv) = measurement;
+      graph.push_back(MyFactor(uv, noise, Symbol('x', i), Symbol('p', j)));
+    }
+    j += 1;
+  }
+
+  // Add a prior on pose x1. This indirectly specifies where the origin is.
+  graph.push_back(
+      PriorFactor<SfM_Camera>(Symbol('x', 0), mydata.cameras[0],
+          noiseModel::Isotropic::Sigma(9, 0.1)));
+
+  // Add a prior on the position of the first landmark to fix the scale
+  graph.push_back(
+      PriorFactor<Point3>(Symbol('p', 0), mydata.tracks[0].p,
+          noiseModel::Isotropic::Sigma(3, 0.1)));
+
+  // Create the data structure to hold the initial estimate to the solution
+  // Intentionally initialize the variables off from the ground truth
+  Values initial;
+  size_t i = 0;
+  BOOST_FOREACH(const SfM_Camera& camera, mydata.cameras)
+    initial.insert(Symbol('x', i++), camera);
+  j = 0;
+  BOOST_FOREACH(const SfM_Track& track, mydata.tracks)
+    initial.insert(Symbol('p', j++), track.p);
+
+  /* Optimize the graph and print results */
+  Values result;
+  try {
+    LevenbergMarquardtParams params;
+    params.setVerbosity("ERROR");
+    LevenbergMarquardtOptimizer lm(graph, initial, params);
+    result = lm.optimize();
+  } catch (exception& e) {
+    cout << e.what();
+  }
+  cout << "final error: " << graph.error(result) << endl;
+
+  return 0;
+}
+/* ************************************************************************* */
+