diff --git a/gtsam_unstable/examples/SmartProjectionFactorTesting.cpp b/gtsam_unstable/examples/SmartProjectionFactorTesting.cpp
new file mode 100644
index 000000000..3421a6d38
--- /dev/null
+++ b/gtsam_unstable/examples/SmartProjectionFactorTesting.cpp
@@ -0,0 +1,350 @@
+/* ----------------------------------------------------------------------------
+
+ * 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 SmartProjectionFactorTesting.cpp
+ * @brief Example usage of SmartProjectionFactor using real datasets
+ * @date August, 2013
+ * @author Luca Carlone
+ */
+
+// Use a map to store landmark/smart factor pairs
+#include <gtsam/base/FastMap.h>
+
+// Both relative poses and recovered trajectory poses will be stored as Pose3 objects
+#include <gtsam/geometry/Pose3.h>
+#include <gtsam/geometry/PinholeCamera.h>
+#include <gtsam/geometry/Cal3Bundler.h>
+
+// Each variable in the system (poses and landmarks) must be identified with a unique key.
+// We can either use simple integer keys (1, 2, 3, ...) or symbols (X1, X2, L1).
+// Here we will use Symbols
+#include <gtsam/inference/Symbol.h>
+
+// We want to use iSAM2 to solve the range-SLAM problem incrementally
+#include <gtsam/nonlinear/ISAM2.h>
+
+// iSAM2 requires as input a set set of new factors to be added stored in a factor graph,
+// and initial guesses for any new variables used in the added factors
+#include <gtsam/nonlinear/Values.h>
+
+// We will use a non-linear solver to batch-initialize from the first 150 frames
+#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
+#include <gtsam/nonlinear/GaussNewtonOptimizer.h>
+
+// In GTSAM, measurement functions are represented as 'factors'. Several common factors
+// have been provided with the library for solving robotics SLAM problems.
+#include <gtsam/slam/PriorFactor.h>
+#include <gtsam_unstable/slam/SmartProjectionFactorsCreator.h>
+#include <gtsam_unstable/slam/GenericProjectionFactorsCreator.h>
+
+// Standard headers, added last, so we know headers above work on their own
+#include <boost/foreach.hpp>
+#include <boost/assign.hpp>
+#include <boost/assign/std/vector.hpp>
+#include <fstream>
+#include <iostream>
+
+using namespace std;
+using namespace gtsam;
+using namespace boost::assign;
+namespace NM = gtsam::noiseModel;
+
+using symbol_shorthand::X;
+using symbol_shorthand::L;
+
+typedef PriorFactor<Pose3> Pose3Prior;
+typedef SmartProjectionFactorsCreator<Pose3, Point3, Cal3_S2> SmartFactorsCreator;
+typedef GenericProjectionFactorsCreator<Pose3, Point3, Cal3_S2> ProjectionFactorsCreator;
+typedef FastMap<Key, int> OrderingMap;
+
+bool debug = false;
+
+// Write key values to file
+void writeValues(string directory_, const Values& values){
+  string filename = directory_ + "out_camera_poses.txt";
+  ofstream fout;
+  fout.open(filename.c_str());
+  fout.precision(20);
+
+  // write out camera poses
+  BOOST_FOREACH(Values::ConstFiltered<Pose3>::value_type key_value, values.filter<Pose3>()) {
+    fout << Symbol(key_value.key).index();
+    const gtsam::Matrix& matrix= key_value.value.matrix();
+    for (size_t row=0; row < 4; ++row) {
+      for (size_t col=0; col < 4; ++col) {
+        fout << " " << matrix(row, col);
+      }
+    }
+    fout << endl;
+  }
+  fout.close();
+
+  if(values.filter<Point3>().size() > 0) {
+    // write landmarks
+    filename = directory_ + "landmarks.txt";
+    fout.open(filename.c_str());
+
+    BOOST_FOREACH(Values::ConstFiltered<Point3>::value_type key_value, values.filter<Point3>()) {
+      fout << Symbol(key_value.key).index();
+      fout << " " << key_value.value.x();
+      fout << " " << key_value.value.y();
+      fout << " " << key_value.value.z();
+      fout << endl;
+    }
+    fout.close();
+
+  }
+}
+
+void optimizeGraphLM(NonlinearFactorGraph &graph, gtsam::Values::shared_ptr graphValues, Values &result, boost::shared_ptr<Ordering> &ordering) {
+  // Optimization parameters
+  LevenbergMarquardtParams params;
+  params.verbosityLM = LevenbergMarquardtParams::TRYLAMBDA;
+  params.verbosity = NonlinearOptimizerParams::ERROR;
+  params.lambdaInitial = 1;
+  params.lambdaFactor = 10;
+  // Profile a single iteration
+//  params.maxIterations = 1;
+  params.maxIterations = 100;
+  std::cout << " LM max iterations: " << params.maxIterations << std::endl;
+  // // params.relativeErrorTol = 1e-5;
+  params.absoluteErrorTol = 1.0;
+  params.verbosityLM = LevenbergMarquardtParams::TRYLAMBDA;
+  params.verbosity = NonlinearOptimizerParams::ERROR;
+  params.linearSolverType = SuccessiveLinearizationParams::MULTIFRONTAL_CHOLESKY;
+
+  cout << "Graph size: " << graph.size() << endl;
+  cout << "Number of variables: " << graphValues->size() << endl;
+  std::cout << " OPTIMIZATION " << std::endl;
+
+  std::cout << "\n\n=================================================\n\n";
+  if (debug) {
+    graph.print("thegraph");
+  }
+  std::cout << "\n\n=================================================\n\n";
+
+  if (ordering && ordering->size() > 0) {
+    if (debug) {
+      std::cout << "Have an ordering\n" << std::endl;
+      BOOST_FOREACH(const Key& key, *ordering) {
+        std::cout << key << " ";
+      }
+      std::cout << std::endl;
+    }
+
+    params.ordering = *ordering;
+
+    //for (int i = 0; i < 3; i++) {
+      LevenbergMarquardtOptimizer optimizer(graph, *graphValues, params);
+      gttic_(GenericProjectionFactorExample_kitti);
+      result = optimizer.optimize();
+      gttoc_(GenericProjectionFactorExample_kitti);
+      tictoc_finishedIteration_();
+    //}
+  } else {
+    std::cout << "Using COLAMD ordering\n" << std::endl;
+    //boost::shared_ptr<Ordering> ordering2(new Ordering()); ordering = ordering2;
+
+    //for (int i = 0; i < 3; i++) {
+      LevenbergMarquardtOptimizer optimizer(graph, *graphValues, params);
+      params.ordering = Ordering::COLAMD(graph);
+      gttic_(SmartProjectionFactorExample_kitti);
+      result = optimizer.optimize();
+      gttoc_(SmartProjectionFactorExample_kitti);
+      tictoc_finishedIteration_();
+    //}
+
+    //*ordering = params.ordering;
+    if (params.ordering) {
+        std::cout << "Graph size: " << graph.size() << " ORdering: " << params.ordering->size() << std::endl;
+        ordering = boost::make_shared<Ordering>(*(new Ordering()));
+        *ordering = *params.ordering;
+    } else {
+        std::cout << "WARNING: NULL ordering!" << std::endl;
+    }
+  }
+}
+
+void optimizeGraphGN(NonlinearFactorGraph &graph, gtsam::Values::shared_ptr graphValues, Values &result) {
+  GaussNewtonParams params;
+  //params.maxIterations = 1;
+  params.verbosity = NonlinearOptimizerParams::DELTA;
+
+  GaussNewtonOptimizer optimizer(graph, *graphValues, params);
+  gttic_(SmartProjectionFactorExample_kitti);
+  result = optimizer.optimize();
+  gttoc_(SmartProjectionFactorExample_kitti);
+  tictoc_finishedIteration_();
+
+}
+
+void optimizeGraphISAM2(NonlinearFactorGraph &graph, gtsam::Values::shared_ptr graphValues, Values &result) {
+  ISAM2 isam;
+  gttic_(SmartProjectionFactorExample_kitti);
+  isam.update(graph, *graphValues);
+  result = isam.calculateEstimate();
+  gttoc_(SmartProjectionFactorExample_kitti);
+  tictoc_finishedIteration_();
+}
+
+// main
+int main(int argc, char** argv) {
+
+  //  unsigned int maxNumLandmarks = 1e+7;
+  //  unsigned int maxNumPoses = 1e+7;
+
+  // Set to true to use SmartProjectionFactor. Otherwise GenericProjectionFactor will be used
+  bool useSmartProjectionFactor = false;
+  bool useLM = true; 
+
+  double linThreshold = -1.0; // negative is disabled
+  double rankTolerance = 1.0;
+
+  bool incrementalFlag = false;
+  int optSkip = 200; // we optimize the graph every optSkip poses
+
+  std::cout << "PARAM SmartFactor: " << useSmartProjectionFactor << std::endl;
+  std::cout << "PARAM LM: " << useLM << std::endl;
+  std::cout << "PARAM linThreshold (negative is disabled): " << linThreshold << std::endl;
+
+  // Get home directory and dataset
+  string HOME = getenv("HOME");
+  string input_dir = HOME + "/data/SfM/BAL/Ladybug/";
+  string datasetName = "problem-1723-156502-pre.txt";
+
+  static SharedNoiseModel pixel_sigma(noiseModel::Unit::Create(2));
+  NonlinearFactorGraph graphSmart, graphProjection;
+
+  gtsam::Values::shared_ptr graphSmartValues(new gtsam::Values());
+  gtsam::Values::shared_ptr graphProjectionValues(new gtsam::Values());
+  gtsam::Values::shared_ptr loadedValues(new gtsam::Values());
+
+  // Read in kitti dataset
+  ifstream fin;
+  fin.open((input_dir+datasetName).c_str());
+  if(!fin) {
+    cerr << "Could not open dataset" << endl;
+    exit(1);
+  }
+
+  // read all measurements
+  cout << "Reading dataset... " << endl;
+  unsigned int numLandmarks = 0, numPoses = 0;
+  Key r, l;
+  double u, v;
+  double x, y, z, rotx, roty, rotz, f, k1, k2;
+  std::vector<Key> landmarkKeys, cameraPoseKeys;
+  Values result;
+  bool optimized = false;
+  boost::shared_ptr<Ordering> ordering(new Ordering());
+
+  // std::vector< boost::shared_ptr<Cal3Bundler> > K_cameras; // TODO: uncomment
+  Cal3_S2::shared_ptr K(new Cal3_S2(1, 1, 0, 0, 0));
+
+  // boost::shared_ptr<Cal3Bundler> Kbund(new Cal3Bundler());// TODO: uncomment
+
+  SmartFactorsCreator smartCreator(pixel_sigma, K, rankTolerance, linThreshold);
+  ProjectionFactorsCreator projectionCreator(pixel_sigma, K);
+
+  // main loop: reads measurements and adds factors (also performs optimization if desired)
+  // r >> pose id
+  // l >> landmark id
+  // (u >> u) >> measurement
+  unsigned int totNumLandmarks=0, totNumPoses=0, totNumMeasurements=0;
+  fin >> totNumPoses >> totNumPoses >> totNumMeasurements;
+
+  std::vector<double> vector_u;
+  std::vector<double> vector_v;
+  std::vector<int> vector_r;
+  std::vector<int> vector_l;
+
+  // read measurements
+  for(unsigned int i = 0; i < totNumMeasurements; i++){
+    fin >> r >> l >> u >> v;
+    vector_u.push_back(u);
+    vector_v.push_back(v);
+    vector_r.push_back(r);
+    vector_l.push_back(l);
+  }
+
+  // create values
+  for(unsigned int i = 0; i < totNumPoses; i++){
+    // R,t,f,k1 and k2.
+    fin >> x >> y >> z >> rotx >> roty >> rotz >> f >> k1 >> k2;
+    // boost::shared_ptr<Cal3Bundler> Kbundler(new Cal3Bundler(f, k1, k2, 0.0, 0.0)); // TODO: uncomment
+    // K_cameras.push_back(Kbundler); // TODO: uncomment
+    Vector3 rotVect(rotx,roty,rotz);
+    loadedValues->insert(Symbol('x',i), Pose3(Rot3::Expmap(rotVect), Point3(x,y,z) ) );
+  }
+
+  // add landmarks in standard projection factors
+  if(!useSmartProjectionFactor){
+    for(unsigned int i = 0; i < totNumLandmarks; i++){
+      fin >> x >> y >> z;
+      loadedValues->insert(Symbol('l',i), Point3(x,y,z) );
+    }
+  }
+
+  // 1: add values and factors to the graph
+  // 1.1: add factors
+  // SMART FACTORS ..
+  for(size_t i = 0; i < vector_u.size(); i++){
+    l = vector_l.at(i);
+    r = vector_r.at(i);
+    u = vector_u.at(i);
+    v = vector_v.at(i);
+
+    if (useSmartProjectionFactor) {
+
+      smartCreator.add(L(l), X(r), Point2(u,v), graphSmart);
+      numLandmarks = smartCreator.getNumLandmarks();
+
+      // Add initial pose value if pose does not exist
+      if (!graphSmartValues->exists<Pose3>(X(r)) && loadedValues->exists<Pose3>(X(r))) {
+        graphSmartValues->insert(X(r), loadedValues->at<Pose3>(X(r)));
+        numPoses++;
+        optimized = false;
+      }
+
+    } else {
+      // or STANDARD PROJECTION FACTORS
+      projectionCreator.add(L(l), X(r), Point2(u,v), pixel_sigma, K, graphProjection);
+      numLandmarks = projectionCreator.getNumLandmarks();
+      optimized = false;
+    }
+  }
+
+  if (!useSmartProjectionFactor) {
+    projectionCreator.update(graphProjection, loadedValues, graphProjectionValues);
+    ordering = projectionCreator.getOrdering();
+  }
+
+  if (useSmartProjectionFactor) {
+    if (useLM)
+      optimizeGraphLM(graphSmart, graphSmartValues, result, ordering);
+    else
+      optimizeGraphISAM2(graphSmart, graphSmartValues, result);
+  } else {
+    if (useLM)
+      optimizeGraphLM(graphProjection, graphProjectionValues, result, ordering);
+    else
+      optimizeGraphISAM2(graphSmart, graphSmartValues, result);
+  }
+  // *graphSmartValues = result; // we use optimized solution as initial guess for the next one
+
+  optimized = true;
+
+  writeValues("./", result);
+
+  // if (1||debug) fprintf(stderr,"%d: %d > %d, %d > %d\n", count, numLandmarks, maxNumLandmarks, numPoses, maxNumPoses);
+  exit(0);
+}
diff --git a/gtsam_unstable/slam/GenericProjectionFactorsCreator.h b/gtsam_unstable/slam/GenericProjectionFactorsCreator.h
index e31d513d9..baa79ff82 100644
--- a/gtsam_unstable/slam/GenericProjectionFactorsCreator.h
+++ b/gtsam_unstable/slam/GenericProjectionFactorsCreator.h
@@ -21,7 +21,7 @@
 
 
 #include <gtsam/geometry/PinholeCamera.h>
-
+#include <gtsam/geometry/Cal3Bundler.h>
 //#include <boost/foreach.hpp>
 //#include <boost/assign.hpp>
 //#include <boost/assign/std/vector.hpp>
@@ -80,6 +80,43 @@ namespace gtsam {
         }
     }
 
+    void add(Key landmarkKey,
+            Key poseKey, Point2 measurement,
+            const SharedNoiseModel& model,
+            const boost::shared_ptr<CALIBRATION>& K,
+            NonlinearFactorGraph &graph) {
+            bool debug = false;
+
+            // Create projection factor
+            ProjectionFactor::shared_ptr projectionFactor(new ProjectionFactor(measurement, model, poseKey, landmarkKey, K));
+
+            // Check if landmark exists in mapping
+            ProjectionFactorMap::iterator pfit = projectionFactors.find(landmarkKey);
+            if (pfit != projectionFactors.end()) {
+              if (debug) fprintf(stderr,"Adding measurement to existing landmark\n");
+
+              // Add projection factor to list of projection factors associated with this landmark
+              (*pfit).second.push_back(projectionFactor);
+
+            } else {
+              if (debug) fprintf(stderr,"New landmark (%d)\n", pfit != projectionFactors.end());
+
+              // Create a new vector of projection factors
+              std::vector<ProjectionFactor::shared_ptr> projectionFactorVector;
+              projectionFactorVector.push_back(projectionFactor);
+
+              // Insert projection factor to NEW list of projection factors associated with this landmark
+              projectionFactors.insert( std::make_pair(landmarkKey, projectionFactorVector) );
+
+              // Add projection factor to graph
+              //graph.push_back(projectionFactor);
+
+              // We have a new landmark
+              numLandmarks++;
+              landmarkKeys.push_back( landmarkKey );
+            }
+        }
+
     void update(NonlinearFactorGraph &graph, gtsam::Values::shared_ptr inputValues, gtsam::Values::shared_ptr outputValues) {
         addTriangulatedLandmarks(graph, inputValues, outputValues);
         updateOrdering(graph);
diff --git a/gtsam_unstable/slam/SmartProjectionHessianFactor.h b/gtsam_unstable/slam/SmartProjectionHessianFactor.h
index 5e175e307..0d6fe551b 100644
--- a/gtsam_unstable/slam/SmartProjectionHessianFactor.h
+++ b/gtsam_unstable/slam/SmartProjectionHessianFactor.h
@@ -21,6 +21,7 @@
 
 #include <gtsam/nonlinear/NonlinearFactor.h>
 #include <gtsam/geometry/PinholeCamera.h>
+#include <gtsam/geometry/Cal3Bundler.h>
 #include <gtsam/geometry/Pose3.h>
 #include <gtsam/linear/HessianFactor.h>
 #include <vector>
diff --git a/gtsam_unstable/slam/tests/testSmartProjectionHessianFactor.cpp b/gtsam_unstable/slam/tests/testSmartProjectionHessianFactor.cpp
index 1361033b3..70dd0a4a8 100644
--- a/gtsam_unstable/slam/tests/testSmartProjectionHessianFactor.cpp
+++ b/gtsam_unstable/slam/tests/testSmartProjectionHessianFactor.cpp
@@ -38,7 +38,9 @@
 #include <gtsam/geometry/Point2.h>
 #include <gtsam/geometry/Cal3DS2.h>
 #include <gtsam/geometry/Cal3_S2.h>
+#include <gtsam/geometry/Cal3Bundler.h>
 #include <gtsam/geometry/SimpleCamera.h>
+#include <gtsam/geometry/PinholeCamera.h>
 
 #include <boost/assign/std/vector.hpp>
 
@@ -70,11 +72,10 @@ Symbol x2('X',  2);
 Symbol x3('X',  3);
 
 static Key poseKey1(x1);
-static Key poseKey2(x2);
 static Point2 measurement1(323.0, 240.0);
 static Pose3 body_P_sensor1(Rot3::RzRyRx(-M_PI_2, 0.0, -M_PI_2), Point3(0.25, -0.10, 1.0));
 
-typedef SmartProjectionHessianFactor<Pose3, Point3> SmartFactor;
+typedef SmartProjectionHessianFactor<Pose3, Point3,Cal3_S2> SmartFactor;
 
 /* ************************************************************************* */
 TEST( SmartProjectionHessianFactor, Constructor) {
@@ -836,6 +837,109 @@ TEST( SmartProjectionHessianFactor, HessianWithRotationDegenerate ){
   EXPECT(assert_equal(hessianFactor->information(), hessianFactorRotTran->information(), 1e-8) );
 }
 
+/* ************************************************************************* */
+//TEST( SmartProjectionHessianFactor, ConstructorWithCal3Bundler) {
+//  SmartProjectionHessianFactor<Pose3,Point3,Cal3Bundler> factor1(rankTol, linThreshold);
+//  Cal3Bundler Kbundler(500, 1e-3, 1e-3, 1000, 2000);
+//  factor1.add(measurement1, poseKey1, model, boost::shared_ptr<Cal3Bundler> &Kbundler);
+//}
+
+/* *************************************************************************/
+//TEST( SmartProjectionHessianFactor, Cal3Bundler ){
+//  // cout << " ************************ SmartProjectionHessianFactor: Cal3Bundler **********************" << endl;
+//
+//  Cal3Bundler Kbundler(500, 1e-3, 1e-3, 1000, 2000);
+//
+//  // create first camera. Looking along X-axis, 1 meter above ground plane (x-y)
+//  Pose3 pose1 = Pose3(Rot3::ypr(-M_PI/2, 0., -M_PI/2), gtsam::Point3(0,0,1));
+//  PinholeCamera<Cal3Bundler> cam1(pose1, Kbundler);
+//
+//  // create second camera 1 meter to the right of first camera
+//  Pose3 pose2 = pose1 * Pose3(Rot3(), Point3(1,0,0));
+//  PinholeCamera<Cal3Bundler> cam2(pose2, Kbundler);
+//
+//  // create third camera 1 meter above the first camera
+//  Pose3 pose3 = pose1 * Pose3(Rot3(), Point3(0,-1,0));
+//  PinholeCamera<Cal3Bundler> cam3(pose3, Kbundler);
+//
+//  // three landmarks ~5 meters infront of camera
+//  Point3 landmark1(5, 0.5, 1.2);
+//  Point3 landmark2(5, -0.5, 1.2);
+//  Point3 landmark3(3, 0, 3.0);
+//
+//  vector<Point2> measurements_cam1, measurements_cam2, measurements_cam3;
+//
+//  // 1. Project three landmarks into three cameras and triangulate
+//  Point2 cam1_uv1 = cam1.project(landmark1);
+//  Point2 cam2_uv1 = cam2.project(landmark1);
+//  Point2 cam3_uv1 = cam3.project(landmark1);
+//  measurements_cam1.push_back(cam1_uv1);
+//  measurements_cam1.push_back(cam2_uv1);
+//  measurements_cam1.push_back(cam3_uv1);
+//
+//  Point2 cam1_uv2 = cam1.project(landmark2);
+//  Point2 cam2_uv2 = cam2.project(landmark2);
+//  Point2 cam3_uv2 = cam3.project(landmark2);
+//  measurements_cam2.push_back(cam1_uv2);
+//  measurements_cam2.push_back(cam2_uv2);
+//  measurements_cam2.push_back(cam3_uv2);
+//
+//  Point2 cam1_uv3 = cam1.project(landmark3);
+//  Point2 cam2_uv3 = cam2.project(landmark3);
+//  Point2 cam3_uv3 = cam3.project(landmark3);
+//  measurements_cam3.push_back(cam1_uv3);
+//  measurements_cam3.push_back(cam2_uv3);
+//  measurements_cam3.push_back(cam3_uv3);
+//
+//  std::vector<Key> views;
+//  views.push_back(x1);
+//  views.push_back(x2);
+//  views.push_back(x3);
+
+//  SmartProjectionHessianFactor<Pose3, Point3, Cal3Bundler>::shared_ptr smartFactor1(new SmartFactor());
+//  smartFactor1->add(measurements_cam1, views, model, &Kbundler);
+//
+//  SmartProjectionHessianFactor<Pose3, Point3, Cal3Bundler>::shared_ptr smartFactor2(new SmartFactor());
+//  smartFactor2->add(measurements_cam2, views, model, &Kbundler);
+//
+//  SmartProjectionHessianFactor<Pose3, Point3, Cal3Bundler>::shared_ptr smartFactor3(new SmartFactor());
+//  smartFactor3->add(measurements_cam3, views, model, &Kbundler);
+//
+//  const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
+//
+//  NonlinearFactorGraph graph;
+//  graph.push_back(smartFactor1);
+//  graph.push_back(smartFactor2);
+//  graph.push_back(smartFactor3);
+//  graph.push_back(PriorFactor<Pose3>(x1, pose1, noisePrior));
+//  graph.push_back(PriorFactor<Pose3>(x2, pose2, noisePrior));
+//
+//  //  Pose3 noise_pose = Pose3(Rot3::ypr(-M_PI/10, 0., -M_PI/10), gtsam::Point3(0.5,0.1,0.3)); // noise from regular projection factor test below
+//  Pose3 noise_pose = Pose3(Rot3::ypr(-M_PI/100, 0., -M_PI/100), gtsam::Point3(0.1,0.1,0.1)); // smaller noise
+//  Values values;
+//  values.insert(x1, pose1);
+//  values.insert(x2, pose2);
+//  // initialize third pose with some noise, we expect it to move back to original pose3
+//  values.insert(x3, pose3*noise_pose);
+//  if(isDebugTest) values.at<Pose3>(x3).print("Smart: Pose3 before optimization: ");
+//
+//  LevenbergMarquardtParams params;
+//  if(isDebugTest) params.verbosityLM = LevenbergMarquardtParams::TRYLAMBDA;
+//  if(isDebugTest) params.verbosity = NonlinearOptimizerParams::ERROR;
+//
+//  Values result;
+//  gttic_(SmartProjectionHessianFactor);
+//  LevenbergMarquardtOptimizer optimizer(graph, values, params);
+//  result = optimizer.optimize();
+//  gttoc_(SmartProjectionHessianFactor);
+//  tictoc_finishedIteration_();
+//
+//  // result.print("results of 3 camera, 3 landmark optimization \n");
+//  if(isDebugTest) result.at<Pose3>(x3).print("Smart: Pose3 after optimization: ");
+//  EXPECT(assert_equal(pose3,result.at<Pose3>(x3)));
+//  if(isDebugTest) tictoc_print_();
+// }
+
 
 /* ************************************************************************* */
 int main() { TestResult tr; return TestRegistry::runAllTests(tr); }