diff --git a/examples/CameraResectioning.cpp b/examples/CameraResectioning.cpp
new file mode 100644
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+++ b/examples/CameraResectioning.cpp
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+/*
+ * @file		CameraResectioning.cpp
+ * @brief   An example of gtsam for solving the camera resectioning problem
+ * @author	Duy-Nguyen Ta
+ * @created	Aug 23, 2011
+ */
+#include <gtsam/nonlinear/Key.h>
+#include <gtsam/geometry/Pose3.h>
+#include <gtsam/geometry/Cal3_S2.h>
+#include <gtsam/geometry/SimpleCamera.h>
+#include <gtsam/nonlinear/LieValues.h>
+#include <gtsam/nonlinear/NonlinearFactor.h>
+#include <gtsam/nonlinear/NonlinearFactorGraph.h>
+#include <gtsam/nonlinear/NonlinearOptimization-inl.h>
+
+using namespace gtsam;
+
+typedef TypedSymbol<Pose3, 'x'> PoseKey;
+typedef LieValues<PoseKey> PoseValues;
+
+/**
+ * Unary factor for the pose.
+ */
+class ResectioningFactor: public NonlinearFactor1<PoseValues, PoseKey> {
+  typedef NonlinearFactor1<PoseValues, PoseKey> Base;
+
+  shared_ptrK K_; // camera's intrinsic parameters
+  Point3 P_; // 3D point on the calibration rig
+  Point2 p_; // 2D measurement of the 3D point
+
+public:
+  ResectioningFactor(const SharedGaussian& model, const PoseKey& key,
+      const shared_ptrK& calib, const Point2& p, const Point3& P) :
+    Base(model, key), K_(calib), P_(P), p_(p) {
+  }
+
+  virtual Vector evaluateError(const Pose3& X, boost::optional<Matrix&> H =
+      boost::none) const {
+    SimpleCamera camera(*K_, X);
+    Point2 reprojectionError(camera.project(P_, H) - p_);
+    return reprojectionError.vector();
+  }
+};
+
+/*******************************************************************************/
+/**
+ * Camera: f = 1.0, Image: 100x100, center: 50.0, 50.0
+ * Pose (ground truth): (Xw, -Yw, -Zw, [0,0,2.0]')
+ * Known landmarks:
+ *    3D Points: (10,10,0) (-10,10,0) (-10,-10,0) (10,-10,0)
+ * Perfect measurements:
+ *    2D Point:  (55,45)   (45,45)    (45,55)     (55,55)
+ */
+int main(int argc, char* argv[]) {
+  /* read camera intrinsic parameters */
+  shared_ptrK calib(new Cal3_S2(1.0, 1.0, 0, 50.0, 50.0));
+
+  /* create keys for variables */
+  // we have only 1 variable to solve: the camera pose
+  PoseKey X(1);
+
+  /* 1. create graph */
+  NonlinearFactorGraph<PoseValues> graph;
+
+  /* 2. add factors to the graph */
+  // add measurement factors
+  SharedDiagonal measurementNoise = sharedSigmas(Vector_(2, 1.0, 1.0));
+  boost::shared_ptr<ResectioningFactor> factor;
+  factor = boost::shared_ptr<ResectioningFactor>(new ResectioningFactor(
+      measurementNoise, X, calib, Point2(55.1, 45.4), Point3(10.0, 10.0, 0.0)));
+  graph.push_back(factor);
+  factor = boost::shared_ptr<ResectioningFactor>(new ResectioningFactor(
+      measurementNoise, X, calib, Point2(45.2, 45.1), Point3(-10.0, 10.0, 0.0)));
+  graph.push_back(factor);
+  factor = boost::shared_ptr<ResectioningFactor>(new ResectioningFactor(
+      measurementNoise, X, calib, Point2(45.3, 55.3), Point3(-10.0, -10.0, 0.0)));
+  graph.push_back(factor);
+  factor = boost::shared_ptr<ResectioningFactor>(new ResectioningFactor(
+      measurementNoise, X, calib, Point2(55.1, 55.2), Point3(10.0, -10.0, 0.0)));
+  graph.push_back(factor);
+
+  /* 3. Create an initial estimate for the camera pose */
+  PoseValues initial;
+  initial.insert(X, Pose3(Rot3(1.,0.,0.,
+                               0.,-1.,0.,
+                               0.,0.,-1.), Point3(0.,0.,2.0)));
+
+  /* 4. Optimize the graph using Levenberg-Marquardt*/
+  PoseValues result = optimize<NonlinearFactorGraph<PoseValues> , PoseValues> (
+      graph, initial);
+  result.print("Final result: ");
+
+  return 0;
+}