74 lines
2.3 KiB
Matlab
74 lines
2.3 KiB
Matlab
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% GTSAM Copyright 2010, Georgia Tech Research Corporation,
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% Atlanta, Georgia 30332-0415
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% All Rights Reserved
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% Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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%
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% See LICENSE for the license information
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%
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% @brief A structure from motion example
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% @author Duy-Nguyen Ta
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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import gtsam.*
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options.triangle = false;
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options.nrCameras = 10;
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options.showImages = false;
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[data,truth] = VisualISAMGenerateData(options);
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measurementNoiseSigma = 1.0;
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pointNoiseSigma = 0.1;
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poseNoiseSigmas = [0.001 0.001 0.001 0.1 0.1 0.1]';
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graph = NonlinearFactorGraph;
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%% Add factors for all measurements
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measurementNoise = noiseModel.Isotropic.Sigma(2,measurementNoiseSigma);
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for i=1:length(data.Z)
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for k=1:length(data.Z{i})
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j = data.J{i}{k};
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graph.add(GenericProjectionFactorCal3_S2(data.Z{i}{k}, measurementNoise, symbol('x',i), symbol('p',j), data.K));
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end
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end
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posePriorNoise = noiseModel.Diagonal.Sigmas(poseNoiseSigmas);
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graph.add(PriorFactorPose3(symbol('x',1), truth.cameras{1}.pose, posePriorNoise));
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pointPriorNoise = noiseModel.Isotropic.Sigma(3,pointNoiseSigma);
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graph.add(PriorFactorPoint3(symbol('p',1), truth.points{1}, pointPriorNoise));
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%% Initial estimate
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initialEstimate = Values;
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for i=1:size(truth.cameras,2)
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pose_i = truth.cameras{i}.pose;
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initialEstimate.insert(symbol('x',i), pose_i);
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end
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for j=1:size(truth.points,2)
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point_j = truth.points{j};
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initialEstimate.insert(symbol('p',j), point_j);
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end
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%% Optimization
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optimizer = LevenbergMarquardtOptimizer(graph, initialEstimate);
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for i=1:5
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optimizer.iterate();
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end
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result = optimizer.values();
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%% Marginalization
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marginals = Marginals(graph, result);
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marginals.marginalCovariance(symbol('p',1));
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marginals.marginalCovariance(symbol('x',1));
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%% Check optimized results, should be equal to ground truth
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for i=1:size(truth.cameras,2)
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pose_i = result.atPose3(symbol('x',i));
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CHECK('pose_i.equals(truth.cameras{i}.pose,1e-5)',pose_i.equals(truth.cameras{i}.pose,1e-5))
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end
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for j=1:size(truth.points,2)
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point_j = result.atPoint3(symbol('p',j));
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CHECK('point_j.equals(truth.points{j},1e-5)',norm(point_j - truth.points{j}) < 1e-5)
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end
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