diff --git a/examples/EssentialViewGraphExample.cpp b/examples/EssentialViewGraphExample.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    EssentialViewGraphExample.cpp
+ * @brief   View-graph calibration on a simulated dataset, a la Sweeney 2015
+ * @author  Frank Dellaert
+ * @date    October 2024
+ */
+
+#include <gtsam/geometry/Cal3_S2.h>
+#include <gtsam/geometry/PinholeCamera.h>
+#include <gtsam/geometry/Point2.h>
+#include <gtsam/geometry/Point3.h>
+#include <gtsam/geometry/Pose3.h>
+#include <gtsam/inference/EdgeKey.h>
+#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
+#include <gtsam/nonlinear/NonlinearFactorGraph.h>
+#include <gtsam/nonlinear/Values.h>
+#include <gtsam/sfm/TransferFactor.h>
+
+#include <vector>
+
+#include "SFMdata.h"
+#include "gtsam/inference/Key.h"
+
+using namespace std;
+using namespace gtsam;
+
+/* ************************************************************************* */
+int main(int argc, char* argv[]) {
+  // Define the camera calibration parameters
+  Cal3_S2 K(50.0, 50.0, 0.0, 50.0, 50.0);
+
+  // Create the set of 8 ground-truth landmarks
+  vector<Point3> points = createPoints();
+
+  // Create the set of 4 ground-truth poses
+  vector<Pose3> poses = posesOnCircle(4, 30);
+
+  // Calculate ground truth fundamental matrices, 1 and 2 poses apart
+  auto F1 = FundamentalMatrix(K, poses[0].between(poses[1]), K);
+  auto F2 = FundamentalMatrix(K, poses[0].between(poses[2]), K);
+
+  // Simulate measurements from each camera pose
+  std::array<std::array<Point2, 8>, 4> p;
+  for (size_t i = 0; i < 4; ++i) {
+    PinholeCamera<Cal3_S2> camera(poses[i], K);
+    for (size_t j = 0; j < 8; ++j) {
+      p[i][j] = camera.project(points[j]);
+    }
+  }
+
+  // This section of the code is inspired by the work of Sweeney et al.
+  // [link](sites.cs.ucsb.edu/~holl/pubs/Sweeney-2015-ICCV.pdf) on view-graph
+  // calibration. The graph is made up of transfer factors that enforce the
+  // epipolar constraint between corresponding points across three views, as
+  // described in the paper. Rather than adding one ternary error term per point
+  // in a triplet, we add three binary factors for sparsity during optimization.
+  // In this version, we only include triplets between 3 successive cameras.
+  NonlinearFactorGraph graph;
+  using Factor = TransferFactor<FundamentalMatrix>;
+
+  for (size_t a = 0; a < 4; ++a) {
+    size_t b = (a + 1) % 4;  // Next camera
+    size_t c = (a + 2) % 4;  // Camera after next
+
+    // Vectors to collect tuples for each factor
+    std::vector<std::tuple<Point2, Point2, Point2>> tuples1, tuples2, tuples3;
+
+    // Collect data for the three factors
+    for (size_t j = 0; j < 8; ++j) {
+      tuples1.emplace_back(p[a][j], p[b][j], p[c][j]);
+      tuples2.emplace_back(p[a][j], p[c][j], p[b][j]);
+      tuples3.emplace_back(p[c][j], p[b][j], p[a][j]);
+    }
+
+    // Add transfer factors between views a, b, and c. Note that the EdgeKeys
+    // are crucial in performing the transfer in the right direction. We use
+    // exactly 8 unique EdgeKeys, corresponding to 8 unknown fundamental
+    // matrices we will optimize for.
+    graph.emplace_shared<Factor>(EdgeKey(a, c), EdgeKey(b, c), tuples1);
+    graph.emplace_shared<Factor>(EdgeKey(a, b), EdgeKey(b, c), tuples2);
+    graph.emplace_shared<Factor>(EdgeKey(a, c), EdgeKey(a, b), tuples3);
+  }
+
+  auto formatter = [](Key key) {
+    EdgeKey edge(key);
+    return (std::string)edge;
+  };
+
+  graph.print("Factor Graph:\n", formatter);
+
+  // Create a delta vector to perturb the ground truth
+  // We can't really go far before convergence becomes problematic :-(
+  Vector7 delta;
+  delta << 1, 2, 3, 4, 5, 6, 7;
+  delta *= 1e-5;
+
+  // Create the data structure to hold the initial estimate to the solution
+  Values initialEstimate;
+  for (size_t a = 0; a < 4; ++a) {
+    size_t b = (a + 1) % 4;  // Next camera
+    size_t c = (a + 2) % 4;  // Camera after next
+    initialEstimate.insert(EdgeKey(a, b), F1.retract(delta));
+    initialEstimate.insert(EdgeKey(a, c), F2.retract(delta));
+  }
+  initialEstimate.print("Initial Estimates:\n", formatter);
+    graph.printErrors(initialEstimate, "errors: ", formatter);
+
+  /* Optimize the graph and print results */
+  LevenbergMarquardtParams params;
+  params.setlambdaInitial(1000.0);  // Initialize lambda to a high value
+  params.setVerbosityLM("SUMMARY");
+  Values result =
+      LevenbergMarquardtOptimizer(graph, initialEstimate, params).optimize();
+
+  cout << "initial error = " << graph.error(initialEstimate) << endl;
+  cout << "final error = " << graph.error(result) << endl;
+
+  result.print("Final results:\n", formatter);
+
+  cout << "Ground Truth F1:\n" << F1.matrix() << endl;
+  cout << "Ground Truth F2:\n" << F2.matrix() << endl;
+
+  return 0;
+}
+/* ************************************************************************* */