101 lines
No EOL
3 KiB
Matlab
101 lines
No EOL
3 KiB
Matlab
function [meanError, all_rot_preds, all_rot_gts, meanErrors, all_errors, rels_all, seq_ids] = calcBiwiError(resDir, gtDir)
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seqNames = {'01','02','03','04','05','06','07','08','09', ...
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'10', '11','12','13','14','15','16','17','18','19', ...
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'20', '21','22','23','24'};
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rotMeanErr = zeros(numel(seqNames),3);
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rotRMS = zeros(numel(seqNames),3);
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rot = cell(1,numel(seqNames));
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rotg = cell(1,numel(seqNames));
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rels_all = [];
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seq_ids = {};
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for i=1:numel(seqNames)
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posesGround = load ([gtDir '/' seqNames{i} '/groundTruthPose.txt']);
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fname = [resDir seqNames{i} '.csv'];
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if(i == 1)
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% First read in the column names
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tab = readtable(fname);
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column_names = tab.Properties.VariableNames;
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confidence_id = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'confidence'));
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rot_ids = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'pose_R'));
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t_ids = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'pose_T'));
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end
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all_params = dlmread(fname, ',', 1, 0);
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T = all_params(:,t_ids);
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tx = T(:,1);
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ty = T(:,2);
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tz = T(:,3);
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rot{i} = all_params(:, rot_ids);
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rels = all_params(:, confidence_id);
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% the reliabilities of head pose
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rels_all = cat(1, rels_all, rels);
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rotg{i} = posesGround(:,[5 6 7]);
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% Correct the first frame so it corresponds to (0,0,0), as slightly
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% different pose might be assumed frontal and this corrects for
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% that
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% Work out the correction matrix for ground truth
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rot_corr_gt = Euler2Rot(rotg{i}(1,:));
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for r_e = 1:size(rotg{i},1)
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rot_curr_gt = Euler2Rot(rotg{i}(r_e,:));
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rot_new_gt = rot_corr_gt' * rot_curr_gt;
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rotg{i}(r_e,:) = Rot2Euler(rot_new_gt);
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end
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% First move the orientation to camera space
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zx = sqrt(tx.^2 + tz.^2);
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eul_x = atan2(ty, zx);
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zy = sqrt(ty.^2 + tz.^2);
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eul_y = -atan2(tx, zy);
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for r_e = 1:size(rot{i},1)
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cam_rot = Euler2Rot([eul_x(r_e), eul_y(r_e), 0]);
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h_rot = Euler2Rot(rot{i}(r_e,:));
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c_rot = cam_rot * h_rot;
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rot{i}(r_e,:) = Rot2Euler(c_rot);
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end
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% Work out the correction matrix for estimates
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rot_corr_est = Euler2Rot(rot{i}(1,:));
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for r_e = 1:size(rot{i},1)
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rot_curr_est = Euler2Rot(rot{i}(r_e,:));
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rot_new_est = rot_corr_est' * rot_curr_est;
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rot{i}(r_e,:) = Rot2Euler(rot_new_est);
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end
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rotg{i} = rotg{i} * 180 / pi;
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rot{i} = rot{i} * 180 / pi;
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rotMeanErr(i,:) = mean(abs((rot{i}(:,:)-rotg{i}(:,:))));
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rotRMS(i,:) = sqrt(mean(((rot{i}(:,:)-rotg{i}(:,:))).^2));
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seq_ids = cat(1, seq_ids, repmat(seqNames(i), size(rot{i},1), 1));
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end
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%%
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meanErrors = rotMeanErr;
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allRot = cell2mat(rot');
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allRotg = cell2mat(rotg');
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meanError = mean(abs((allRot(:,:)-allRotg(:,:))));
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all_errors = abs(allRot-allRotg);
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rmsError = sqrt(mean(((allRot(:,:)-allRotg(:,:))).^2));
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errorVariance = std(abs((allRot(:,:)-allRotg(:,:))));
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all_rot_preds = allRot;
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all_rot_gts = allRotg; |