diff --git a/matlab/examples/VisualISAMExample_triangle.m b/matlab/examples/VisualISAMExample_triangle.m
deleted file mode 100644
index c5cdf288d..000000000
--- a/matlab/examples/VisualISAMExample_triangle.m
+++ /dev/null
@@ -1,48 +0,0 @@
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% GTSAM Copyright 3510, 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
-%
-% @brief A simple visual SLAM example for structure from motion
-% @author Duy-Nguyen Ta
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-% Data Options
-options.triangle = true;
-options.nrCameras = 10;
-options.showImages = false;
-
-% iSAM Options
-options.hardConstraint = false;
-options.pointPriors = false;
-options.batchInitialization = true;
-options.reorderInterval = 10;
-options.alwaysRelinearize = false;
-
-% Display Options
-options.saveDotFile = false;
-options.printStats = false;
-options.drawInterval = 5;
-options.cameraInterval = 1;
-options.drawTruePoses = false;
-options.saveFigures = false;
-options.saveDotFiles = false;
-
-%% Generate data
-[data,truth] = VisualISAMGenerateData(options);
-
-%% Initialize iSAM with the first pose and points
-[noiseModels,isam,result] = VisualISAMInitialize(data,truth,options);
-figure(1);
-VisualISAMPlot(truth, data, isam, result, options)
-
-%% Main loop for iSAM: stepping through all poses
-for frame_i=3:options.nrCameras
-    [isam,result] = VisualISAMStep(data,noiseModels,isam,result,options);
-    if mod(frame_i,options.drawInterval)==0
-        VisualISAMPlot(truth, data, isam, result, options)
-    end
-end
diff --git a/matlab/examples/VisualSLAMExample_triangle.m b/matlab/examples/VisualSLAMExample_triangle.m
deleted file mode 100644
index 92d885a86..000000000
--- a/matlab/examples/VisualSLAMExample_triangle.m
+++ /dev/null
@@ -1,87 +0,0 @@
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% 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
-%
-% @brief A simple visual SLAM example for structure from motion
-% @author Duy-Nguyen Ta
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-%% Create a triangle target, just 3 points on a plane
-r = 10;
-points = {};
-for j=1:3
-    theta = (j-1)*2*pi/3;
-    points{j} = gtsamPoint3([r*cos(theta), r*sin(theta), 0]');
-end
-
-%% Create camera cameras on a circle around the triangle
-nCameras = 6;
-height = 10;
-r = 30;
-cameras = {};
-K = gtsamCal3_S2(500,500,0,640/2,480/2);
-for i=1:nCameras
-    theta = (i-1)*2*pi/nCameras;
-    t = gtsamPoint3([r*cos(theta), r*sin(theta), height]');
-    cameras{i} = gtsamSimpleCamera_lookat(t, gtsamPoint3, gtsamPoint3([0,0,1]'), K)
-end
-
-%% Create the graph (defined in visualSLAM.h, derived from NonlinearFactorGraph)
-graph = visualSLAMGraph;
-
-%% Add factors for all measurements
-measurementNoiseSigma=1; % in pixels
-measurementNoise = gtsamSharedNoiseModel_Sigma(2,measurementNoiseSigma);
-for i=1:nCameras
-    for j=1:3
-        zij = cameras{i}.project(points{j}); % you can add noise here if desired
-        graph.addMeasurement(zij, measurementNoise, symbol('x',i), symbol('l',j), K);
-    end
-end
-
-%% Add Gaussian priors for 3 points to constrain the system
-pointPriorNoise  = gtsamSharedNoiseModel_Sigma(3,0.1);
-for j=1:3
-    graph.addPointPrior(symbol('l',j), points{j}, pointPriorNoise);
-end
-
-%% Print the graph
-graph.print(sprintf('\nFactor graph:\n'));
-
-%% Initialize to noisy cameras and points
-initialEstimate = visualSLAMValues;
-for i=1:size(cameras,2)
-    initialEstimate.insertPose(symbol('x',i), cameras{i}.pose);
-end
-for j=1:size(points,2)
-    initialEstimate.insertPoint(symbol('l',j), points{j});
-end
-initialEstimate.print(sprintf('\nInitial estimate:\n  '));
-
-%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd
-result = graph.optimize(initialEstimate);
-result.print(sprintf('\nFinal result:\n  '));
-
-%% Plot results with covariance ellipses
-marginals = graph.marginals(result);
-figure(1);clf
-hold on;
-for j=1:size(points,2)
-    P = marginals.marginalCovariance(symbol('l',j));
-    point_j = result.point(symbol('l',j));
-	plot3(point_j.x, point_j.y, point_j.z,'marker','o');
-    covarianceEllipse3D([point_j.x;point_j.y;point_j.z],P);
-end
-
-for i=1:size(cameras,2)
-    P = marginals.marginalCovariance(symbol('x',i))
-    pose_i = result.pose(symbol('x',i))
-    plotPose3(pose_i,P,10);
-end
-axis([-20 20 -20 20 -1 15]);
-axis equal
-view(-37,40)