v01

thirdparty/opengv/matlab/plot_arun_error.m

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+%% Reset everything
+
+clear all;
+clc;
+close all;
+addpath('helpers');
+
+%% Configure the benchmark
+
+% noncentral case
+cam_number = 4;
+% Getting 17 points, and testing all algorithms with the respective number of points
+pt_number = 8;
+% noise test, so no outliers
+outlier_fraction = 0.0;
+% repeat 1000 tests per noise level
+iterations = 10000;
+
+% The algorithms we want to test
+algorithms = { 'ge2' };
+% This defines the number of points used for every algorithm
+indices = { [1:1:8] };
+% The name of the algorithms in the final plots
+names = { 'arun (8pt)' };
+
+% The maximum noise to analyze
+noise = 0.5;
+
+%% Run the benchmark
+
+%Run the experiment
+    
+rotation_errors = zeros(1,iterations);
+    
+counter = 0;
+    
+for i=1:iterations
+
+    % generate experiment        
+    [v1,v2,t,R] = create2D2DOmniExperiment(pt_number,cam_number,noise,outlier_fraction);
+    [t_perturbed,R_perturbed] = perturb(t,R,0.01);
+    T_perturbed = [R_perturbed,t_perturbed];
+    T_init = [eye(3),zeros(3,1)];
+    T_gt = [R,t];
+        
+    Out = opengv(algorithms{1},indices{1},v1,v2,T_perturbed);
+
+    rotation_error = evaluateRotationError( R, Out(1:3,1:3) );
+    rotation_errors(1,i) = rotation_error;
+	
+        
+    counter = counter + 1;
+    if counter == 100
+        counter = 0;
+        display(['Iteration ' num2str(i) ' of ' num2str(iterations) '(noise level ' num2str(noise) ')']);
+    end        
+end
+
+%% Plot the results
+hist(rad2deg(rotation_errors))
+xlabel('rotation error [deg]')
+ylabel('occurence')
+grid on