86 lines
2.9 KiB
Matlab
86 lines
2.9 KiB
Matlab
function [meanError, all_rot_preds, all_rot_gts, meanErrors, all_errors, rels_all, seq_ids] = calcIctError(resDir, gtDir)
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%CALCICTERROR Summary of this function goes here
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% Detailed explanation goes here
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polhemus = 'polhemusNorm.csv';
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sequences = dir([resDir '*.csv']);
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rotMeanErr = zeros(numel(sequences),3);
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rotRMS = zeros(numel(sequences),3);
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rot = cell(1,numel(sequences));
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rotg = cell(1,numel(sequences));
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rels_all = [];
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seq_ids = {};
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for i = 1:numel(sequences)
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[~, name,~] = fileparts(sequences(i).name);
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fname = [resDir '/' sequences(i).name];
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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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end
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all_params = dlmread(fname, ',', 1, 0);
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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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[txg tyg tzg rxg ryg rzg] = textread([gtDir name '/' polhemus], '%f,%f,%f,%f,%f,%f');
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rotg{i} = [rxg ryg rzg];
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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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% 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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% Convert the ground truth and estimates to degrees
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rot{i} = rot{i} * (180/ pi);
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rotg{i} = rotg{i} * (180/ pi);
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% Now compute the errors
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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({[name 'ict']}, size(rot{i},1), 1));
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end
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allRot = cell2mat(rot');
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allRotg = cell2mat(rotg');
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meanErrors = rotMeanErr;
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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 = var(abs((allRot(:,:)-allRotg(:,:))));
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all_rot_preds = allRot;
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all_rot_gts = allRotg;
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end
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