101 lines
2.8 KiB
Matlab
101 lines
2.8 KiB
Matlab
function pts2dTracksMono = points2DTrackMonocular(K, cameraPoses, imageSize, cylinders)
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% Assess how accurately we can reconstruct points from a particular monocular camera setup.
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% After creation of the factor graph for each track, linearize it around ground truth.
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% There is no optimization
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% @author: Zhaoyang Lv
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import gtsam.*
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%% create graph
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graph = NonlinearFactorGraph;
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%% create the noise factors
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poseNoiseSigmas = [0.001 0.001 0.001 0.1 0.1 0.1]';
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posePriorNoise = noiseModel.Diagonal.Sigmas(poseNoiseSigmas);
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measurementNoiseSigma = 1.0;
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measurementNoise = noiseModel.Isotropic.Sigma(2, measurementNoiseSigma);
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cameraPosesNum = length(cameraPoses);
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%% add measurements and initial camera & points values
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pointsNum = 0;
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cylinderNum = length(cylinders);
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for i = 1:cylinderNum
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pointsNum = pointsNum + length(cylinders{i}.Points);
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end
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pts3d = cell(cameraPosesNum, 1);
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initialEstimate = Values;
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initialized = false;
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for i = 1:cameraPosesNum
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% add a constraint on the starting pose
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cameraPose = cameraPoses{i};
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pts3d{i} = cylinderSampleProjection(K, cameraPose, imageSize, cylinders);
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if ~initialized
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graph.add(PriorFactorPose3(symbol('x', 1), cameraPose, posePriorNoise));
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initialized = true;
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end
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for j = 1:length(pts3d{i}.Z)
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if isempty(pts3d{i}.Z{j})
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continue;
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end
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graph.add(GenericProjectionFactorCal3_S2(pts3d{i}.Z{j}, ...
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measurementNoise, symbol('x', i), symbol('p', j), K) );
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end
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end
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%% initialize cameras and points close to ground truth
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for i = 1:cameraPosesNum
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pose_i = cameraPoses{i}.retract(0.1*randn(6,1));
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initialEstimate.insert(symbol('x', i), pose_i);
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end
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ptsIdx = 0;
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for i = 1:length(cylinders)
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for j = 1:length(cylinders{i}.Points)
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ptsIdx = ptsIdx + 1;
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point_j = cylinders{i}.Points{j}.retract(0.1*randn(3,1));
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initialEstimate.insert(symbol('p', ptsIdx), point_j);
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end
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end
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%% Print the graph
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graph.print(sprintf('\nFactor graph:\n'));
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marginals = Marginals(graph, initialEstimate);
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%% get all the points track information
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% currently throws the Indeterminant linear system exception
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ptx = 1;
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for k = 1:cameraPosesNum
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for i = 1:length(cylinders)
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for j = 1:length(cylinders{i}.Points)
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if isempty(pts3d{k}.index{i}{j})
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continue;
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end
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idx = pts3d{k}.index{i}{j};
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pts2dTracksMono.pt3d{ptx} = pts3d{k}.data{idx};
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pts2dTracksMono.Z{ptx} = pts3d{k}.Z{idx};
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pts2dTracksMono.cov{ptx} = marginals.marginalCovariance(symbol('p',idx));
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ptx = ptx + 1;
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end
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end
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end
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%% plot the result with covariance ellipses
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hold on;
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%plot3DPoints(initialEstimate, [], marginals);
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%plot3DTrajectory(initialEstimate, '*', 1, 8, marginals);
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plot3DTrajectory(initialEstimate, '*', 1, 8);
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view(3);
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end
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