89 lines
2.7 KiB
Matlab
89 lines
2.7 KiB
Matlab
function [ error_per_image ] = compute_brow_error( ground_truth_all, detected_points_all, occluded )
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%compute_error
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% compute the average point-to-point Euclidean error of right eye normalized by the
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% inter-ocular distance (measured as the Euclidean distance between the
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% outer corners of the eyes)
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%
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% Inputs:
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% grounth_truth_all, size: num_of_points x 2 x num_of_images
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% detected_points_all, size: num_of_points x 2 x num_of_images
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% Output:
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% error_per_image, size: num_of_images x 1
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brow_inds_from_68 = 18:27;
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brow_inds_from_49 = 1:10;
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brow_inds_from_66 = 18:27;
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num_of_images = size(ground_truth_all,3);
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num_points_gt = size(ground_truth_all,1);
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num_points_det = size(detected_points_all,1);
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error_per_image = zeros(num_of_images,1);
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for i =1:num_of_images
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if(num_points_det == 10)
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detected_points = detected_points_all(:,:,i);
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elseif(num_points_det == 68)
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detected_points = detected_points_all(brow_inds_from_68,:,i);
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elseif(num_points_det == 66)
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detected_points = detected_points_all(brow_inds_from_66,:,i);
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elseif(num_points_det == 49)
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detected_points = detected_points_all(brow_inds_from_49,:,i);
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end
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ground_truth_points = ground_truth_all(:,:,i);
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if(num_points_gt == 66 || num_points_gt == 68)
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interocular_distance = norm(ground_truth_points(37,:)-ground_truth_points(46,:));
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ground_truth_points = ground_truth_points(brow_inds_from_68,:,:);
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else
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interocular_distance = norm(ground_truth_points(37-17,:)-ground_truth_points(46-17,:));
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ground_truth_points = ground_truth_points(brow_inds_from_68,:,:);
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end
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sum=0;
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for j=1:size(detected_points,1)
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if(j== 1 || j == 5 || j == 6 || j == 10)
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% eye corners should align perfectly
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sum = sum + norm(detected_points(j,:)-ground_truth_points(j,:));
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else
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sum = sum + point_to_segments(detected_points(j,:), ground_truth_points(j-1:j+1,:));
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end
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end
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error_per_image(i) = sum/(size(detected_points,1)*interocular_distance);
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end
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if(nargin > 2)
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error_per_image = error_per_image(~occluded);
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end
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end
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function seg_dist = point_to_segments(point, segments)
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seg_dists = zeros(size(segments, 1)-1,1);
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for i=1:size(segments, 1)-1
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vec1 = point - segments(i,:);
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vec2 = segments(i+1,:) - segments(i,:);
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d = (vec1 * vec2') / (norm(vec2)^2);
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if(d < 0)
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seg_dists(i) = norm(vec1);
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elseif(d > 1)
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seg_dists(i) = norm(point - segments(i+1,:));
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else
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seg_dists(i) = sqrt( norm(vec1)^2 - norm(d * vec2)^2);
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end
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end
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seg_dist = min(seg_dists);
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end |