diff --git a/examples/VisualISAMExample.cpp b/examples/VisualISAMExample.cpp
index dca24dba5..38fe1dd35 100644
--- a/examples/VisualISAMExample.cpp
+++ b/examples/VisualISAMExample.cpp
@@ -53,10 +53,8 @@ int main(int argc, char* argv[]) {
   	// First pose with prior factor
   	newFactors.addPosePrior(X(0), data.poses[0], data.noiseX);
 
-  	// Second pose with odometry measurement, simulated by adding Gaussian noise to the ground-truth.
-  	Pose3 odoMeasurement =  data.odometry*Pose3::Expmap(data.noiseX->sample());
-  	newFactors.push_back( boost::shared_ptr<BetweenFactor<Pose3> >(
-  	  			new BetweenFactor<Pose3>(X(0), X(1), odoMeasurement, data.noiseX)));
+  	// Second pose with odometry measurement
+  	newFactors.addOdometry(X(0), X(1), data.odometry, data.noiseX);
 
   	// Visual measurements at both poses
   	for (size_t i=0; i<2; ++i) {
@@ -67,13 +65,12 @@ int main(int argc, char* argv[]) {
 
   	// Initial values for the first two poses, simulated with Gaussian noise
   	Values initials;
-  	Pose3 pose0Init = data.poses[0]*Pose3::Expmap(data.noiseX->sample());
-  	initials.insert(X(0), pose0Init);
-  	initials.insert(X(1), pose0Init*odoMeasurement);
+  	initials.insert(X(0), data.poses[0]);
+  	initials.insert(X(1), data.poses[0]*data.odometry);
 
-  	// Initial values for the landmarks, simulated with Gaussian noise
+  	// Initial values for the landmarks
   	for (size_t j=0; j<data.points.size(); ++j)
-  		initials.insert(L(j), data.points[j] + Point3(data.noiseL->sample()));
+  		initials.insert(L(j), data.points[j]);
 
   	// Update ISAM the first time and obtain the current estimate
   	isam.update(newFactors, initials);
@@ -87,9 +84,8 @@ int main(int argc, char* argv[]) {
   for (size_t i=2; i<data.poses.size(); ++i) {
   	visualSLAM::Graph newFactors;
   	// Factor for odometry measurements, simulated by adding Gaussian noise to the ground-truth.
-  	Pose3 odoMeasurement =  data.odometry*Pose3::Expmap(data.noiseX->sample());
-  	newFactors.push_back( boost::shared_ptr<BetweenFactor<Pose3> >(
-  			new BetweenFactor<Pose3>(X(i-1), X(i), odoMeasurement, data.noiseX)));
+  	Pose3 odoMeasurement =  data.odometry;
+  	newFactors.addOdometry(X(i-1), X(i), data.odometry, data.noiseX);
   	// Factors for visual measurements
   	for (size_t j=0; j<data.z[i].size(); ++j) {
   		newFactors.addMeasurement(data.z[i][j], data.noiseZ, X(i), L(j), data.sK);
@@ -97,7 +93,7 @@ int main(int argc, char* argv[]) {
 
     // Initial estimates for the new node Xi, simulated by Gaussian noises
   	Values initials;
-  	initials.insert(X(i), currentEstimate.at<Pose3>(X(i-1))*odoMeasurement);
+  	initials.insert(X(i), currentEstimate.at<Pose3>(X(i-1))*data.odometry);
 
   	// update ISAM
   	isam.update(newFactors, initials);
diff --git a/examples/VisualSLAMData.h b/examples/VisualSLAMData.h
index 155a137d8..88fb576fe 100644
--- a/examples/VisualSLAMData.h
+++ b/examples/VisualSLAMData.h
@@ -66,20 +66,19 @@ struct VisualSLAMExampleData {
 		double theta = 0.0;
 		double r = 30.0;
 		for (int i=0; i<n; ++i, theta += 2*M_PI/n) {
-			data.poses.push_back(gtsam::Pose3(
-					gtsam::Rot3(-sin(theta), 0.0, -cos(theta),
-											cos(theta), 0.0, -sin(theta),
-											0.0, -1.0, 0.0),
-					gtsam::Point3(r*cos(theta), r*sin(theta), 0.0)));
+			Point3 C = gtsam::Point3(r*cos(theta), r*sin(theta), 0.0);
+			SimpleCamera camera = SimpleCamera::lookat(C, Point3(), Point3(0,0,1));
+			data.poses.push_back(camera.pose());
 		}
 		data.odometry = data.poses[0].between(data.poses[1]);
 
-		// Simulated measurements with Gaussian noise
+		// Simulated measurements, possibly with Gaussian noise
 		data.noiseZ = gtsam::sharedSigma(2, 1.0);
 		for (size_t i=0; i<data.poses.size(); ++i) {
 			for (size_t j=0; j<data.points.size(); ++j) {
 				gtsam::SimpleCamera camera(data.poses[i], *data.sK);
-				data.z[i].push_back(camera.project(data.points[j]) + gtsam::Point2(data.noiseZ->sample()));
+				data.z[i].push_back(camera.project(data.points[j])
+						/*+ gtsam::Point2(data.noiseZ->sample()))*/); // you can add noise as desired
 			}
 		}
 		data.noiseX = gtsam::sharedSigmas(gtsam::Vector_(6, 0.001, 0.001, 0.001, 0.1, 0.1, 0.1));
diff --git a/examples/VisualSLAMExample.cpp b/examples/VisualSLAMExample.cpp
index 90391bf90..1fc343203 100644
--- a/examples/VisualSLAMExample.cpp
+++ b/examples/VisualSLAMExample.cpp
@@ -49,9 +49,9 @@ int main(int argc, char* argv[]) {
   /* 3. Initial estimates for variable nodes, simulated by Gaussian noises */
   Values initial;
   for (size_t i=0; i<data.poses.size(); ++i)
-  	initial.insert(X(i), data.poses[i]*Pose3::Expmap(data.noiseX->sample()));
+  	initial.insert(X(i), data.poses[i]/* *Pose3::Expmap(data.noiseX->sample())*/); // you can add noise if you want
   for (size_t j=0; j<data.points.size(); ++j)
-  	initial.insert(L(j), data.points[j] + Point3(data.noiseL->sample()));
+  	initial.insert(L(j), data.points[j] /*+ Point3(data.noiseL->sample())*/); // you can add noise if you want
   initial.print("Intial Estimates: ");
 
   /* 4. Optimize the graph and print results */