34 lines
1.2 KiB
Matlab
34 lines
1.2 KiB
Matlab
function [ error_per_image ] = compute_error( ground_truth_all, detected_points_all )
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%compute_error
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% compute the average point-to-point Euclidean error 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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num_of_images = size(ground_truth_all,3);
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num_of_points = size(ground_truth_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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detected_points = detected_points_all(:,:,i);
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ground_truth_points = ground_truth_all(:,:,i);
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if(num_of_points == 66 || num_of_points == 68)
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interocular_distance = norm(ground_truth_points(37,:)-ground_truth_points(46,:));
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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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end
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sum=0;
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for j=1:num_of_points
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sum = sum+norm(detected_points(j,:)-ground_truth_points(j,:));
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end
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error_per_image(i) = sum/(num_of_points*interocular_distance);
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end
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end
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