v01
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119
thirdparty/opengv/matlab/helpers/createMulti2D2DExperiment.m
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119
thirdparty/opengv/matlab/helpers/createMulti2D2DExperiment.m
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function [v1, v2, cam_offsets, t, R ] = createMulti2D2DExperiment( pt_per_cam, cam_number, noise, outlier_fraction )
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%% generate the camera system
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avg_cam_distance = 0.5;
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cam_offsets = zeros(3,cam_number);
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%cam_rotations = zeros(3,cam_number*3);
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if cam_number == 1
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cam_offsets = zeros(3,1);
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%cam_rotations = eye(3);
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else
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for i=1:cam_number
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cam_offsets(:,i) = avg_cam_distance * generateRandomR() * [1.0; 0.0; 0.0];
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%cam_rotations(:,(i-1)*3+1:(i-1)*3+3) = generateRandomR();
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end
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end
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%% generate random view-points
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max_parallax = 2.0;
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max_rotation = 0.5;
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position1 = zeros(3,1);
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rotation1 = eye(3);
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position2 = max_parallax * 2.0 * (rand(3,1) - repmat(0.5,3,1));
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rotation2 = generateBoundedR(max_rotation);
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%% Generate random point-clouds
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minDepth = 4.0;
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maxDepth = 8.0;
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p = cell([cam_number 1]);
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for cam=1:cam_number
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normalizedPoints = 2.0*(rand(3,pt_per_cam)-repmat(0.5,3,pt_per_cam));
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norms = sqrt(sum(normalizedPoints.*normalizedPoints));
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directions = normalizedPoints./repmat(norms,3,1);
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p{cam,1} = (maxDepth-minDepth) * normalizedPoints + minDepth * directions;
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end
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%% Now create the correspondences by looping through the cameras
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focal_length = 800.0;
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v1 = cell([cam_number 1]);
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v2 = cell([cam_number 1]);
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for cam=1:cam_number
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v1{cam,1} = zeros(3,pt_per_cam);
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v2{cam,1} = zeros(3,pt_per_cam);
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for i=1:pt_per_cam
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cam_offset = cam_offsets(:,cam);
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%cam_rotation = cam_rotations(:,(cam-1)*3+1:(cam-1)*3+3);
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body_point1 = rotation1' * (p{cam,1}(:,i)-position1);
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body_point2 = rotation2' * (p{cam,1}(:,i)-position2);
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% we actually omit the cam rotation here by unrotating the bearing
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% vectors already
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bearingVector1 = body_point1 - cam_offset;
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bearingVector2 = body_point2 - cam_offset;
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bearingVector1_norm = norm(bearingVector1);
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bearingVector2_norm = norm(bearingVector2);
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bearingVector1 = bearingVector1/bearingVector1_norm;
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bearingVector2 = bearingVector2/bearingVector2_norm;
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% add noise to the bearing vectors here
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bearingVector1_noisy = addNoise(bearingVector1,focal_length,noise);
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bearingVector2_noisy = addNoise(bearingVector2,focal_length,noise);
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% store the normalized bearing vectors along with the cameras they are
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% being seen (we create correspondences that always originate from the
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% same camera, you should not change this in this experiment!)
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bearingVector1_norm = norm(bearingVector1_noisy);
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bearingVector2_norm = norm(bearingVector2_noisy);
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v1{cam,1}(:,i) = bearingVector1_noisy./bearingVector1_norm;
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v2{cam,1}(:,i) = bearingVector2_noisy./bearingVector2_norm;
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end
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end
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%% Add outliers
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outliers_per_cam = floor(outlier_fraction*pt_per_cam);
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if outliers_per_cam > 0
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for cam=1:cam_number
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for i=1:outliers_per_cam
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cam_offset = cam_offsets(:,cam);
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%cam_rotation = cam_rotations(:,(cam-1)*3+1:(cam-1)*3+3);
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%generate random point
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normalizedPoint = 2.0*(rand(3,1)-repmat(0.5,3,1));
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norm1 = sqrt(sum(normalizedPoint.*normalizedPoint));
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direction = normalizedPoint./norm1;
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point = (maxDepth-minDepth) * normalizedPoint + minDepth * direction;
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body_point2 = rotation2' * (point-position2);
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% store the point (no need to add noise)
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bearingVector2 = body_point2 - cam_offset;
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bearingVector2_norm = norm(bearingVector2);
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v2{cam,1}(:,i) = bearingVector2./bearingVector2_norm;
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end
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end
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end
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%% compute relative translation and rotation
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R = rotation1' * rotation2;
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t = rotation1' * (position2 - position1);
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