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function [v1, v2, cam_offsets, t, R ] = createMulti2D2DExperiment( pt_per_cam, cam_number, noise, outlier_fraction )
%% generate the camera system
avg_cam_distance = 0.5;
cam_offsets = zeros(3,cam_number);
%cam_rotations = zeros(3,cam_number*3);
if cam_number == 1
cam_offsets = zeros(3,1);
%cam_rotations = eye(3);
else
for i=1:cam_number
cam_offsets(:,i) = avg_cam_distance * generateRandomR() * [1.0; 0.0; 0.0];
%cam_rotations(:,(i-1)*3+1:(i-1)*3+3) = generateRandomR();
end
end
%% generate random view-points
max_parallax = 2.0;
max_rotation = 0.5;
position1 = zeros(3,1);
rotation1 = eye(3);
position2 = max_parallax * 2.0 * (rand(3,1) - repmat(0.5,3,1));
rotation2 = generateBoundedR(max_rotation);
%% Generate random point-clouds
minDepth = 4.0;
maxDepth = 8.0;
p = cell([cam_number 1]);
for cam=1:cam_number
normalizedPoints = 2.0*(rand(3,pt_per_cam)-repmat(0.5,3,pt_per_cam));
norms = sqrt(sum(normalizedPoints.*normalizedPoints));
directions = normalizedPoints./repmat(norms,3,1);
p{cam,1} = (maxDepth-minDepth) * normalizedPoints + minDepth * directions;
end
%% Now create the correspondences by looping through the cameras
focal_length = 800.0;
v1 = cell([cam_number 1]);
v2 = cell([cam_number 1]);
for cam=1:cam_number
v1{cam,1} = zeros(3,pt_per_cam);
v2{cam,1} = zeros(3,pt_per_cam);
for i=1:pt_per_cam
cam_offset = cam_offsets(:,cam);
%cam_rotation = cam_rotations(:,(cam-1)*3+1:(cam-1)*3+3);
body_point1 = rotation1' * (p{cam,1}(:,i)-position1);
body_point2 = rotation2' * (p{cam,1}(:,i)-position2);
% we actually omit the cam rotation here by unrotating the bearing
% vectors already
bearingVector1 = body_point1 - cam_offset;
bearingVector2 = body_point2 - cam_offset;
bearingVector1_norm = norm(bearingVector1);
bearingVector2_norm = norm(bearingVector2);
bearingVector1 = bearingVector1/bearingVector1_norm;
bearingVector2 = bearingVector2/bearingVector2_norm;
% add noise to the bearing vectors here
bearingVector1_noisy = addNoise(bearingVector1,focal_length,noise);
bearingVector2_noisy = addNoise(bearingVector2,focal_length,noise);
% store the normalized bearing vectors along with the cameras they are
% being seen (we create correspondences that always originate from the
% same camera, you should not change this in this experiment!)
bearingVector1_norm = norm(bearingVector1_noisy);
bearingVector2_norm = norm(bearingVector2_noisy);
v1{cam,1}(:,i) = bearingVector1_noisy./bearingVector1_norm;
v2{cam,1}(:,i) = bearingVector2_noisy./bearingVector2_norm;
end
end
%% Add outliers
outliers_per_cam = floor(outlier_fraction*pt_per_cam);
if outliers_per_cam > 0
for cam=1:cam_number
for i=1:outliers_per_cam
cam_offset = cam_offsets(:,cam);
%cam_rotation = cam_rotations(:,(cam-1)*3+1:(cam-1)*3+3);
%generate random point
normalizedPoint = 2.0*(rand(3,1)-repmat(0.5,3,1));
norm1 = sqrt(sum(normalizedPoint.*normalizedPoint));
direction = normalizedPoint./norm1;
point = (maxDepth-minDepth) * normalizedPoint + minDepth * direction;
body_point2 = rotation2' * (point-position2);
% store the point (no need to add noise)
bearingVector2 = body_point2 - cam_offset;
bearingVector2_norm = norm(bearingVector2);
v2{cam,1}(:,i) = bearingVector2./bearingVector2_norm;
end
end
end
%% compute relative translation and rotation
R = rotation1' * rotation2;
t = rotation1' * (position2 - position1);
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