sustaining_gazes/matlab_version/demo/face_image_demo_eyes.m

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clear
addpath('../PDM_helpers/');
addpath(genpath('../fitting/'));
addpath('../models/');
addpath(genpath('../face_detection'));
addpath('../CCNF/');
%% loading the patch experts
[clmParams, pdm] = Load_CLM_params_wild();
% An accurate CCNF (or CLNF) model
[patches] = Load_Patch_Experts( '../models/general/', 'ccnf_patches_*_general.mat', [], [], clmParams);
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% A simpler (but less accurate SVR)
% [patches] = Load_Patch_Experts( '../models/general/', 'svr_patches_*_general.mat', [], [], clmParams);
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% Loading eye PDM and patch experts
[clmParams_eye, pdm_right_eye, pdm_left_eye] = Load_CLM_params_eye_28();
[patches_right_eye] = Load_Patch_Experts( '../models/hierarch/', 'ccnf_patches_*_synth_right_eye.mat', [], [], clmParams_eye);
[patches_left_eye] = Load_Patch_Experts( '../models/hierarch/', 'ccnf_patches_*_synth_left_eye.mat', [], [], clmParams_eye);
clmParams_eye.multi_modal_types = patches_right_eye(1).multi_modal_types;
right_eye_inds = [43,44,45,46,47,48];
left_eye_inds = [37,38,39,40,41,42];
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right_eye_inds_synth = [9 11 13 15 17 19];
left_eye_inds_synth = [9 11 13 15 17 19];
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clmParams.multi_modal_types = patches(1).multi_modal_types;
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%%
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% root_dir = 'C:\Users\Tadas\Dropbox\AAM\test data\gaze_original\p00/';
% images = dir([root_dir, '*.jpg']);
%root_dir = './sample_eye_imgs/';
%images = dir([root_dir, '/*.png']);
root_dir = '../../samples/';
images = dir([root_dir, '*.jpg']);
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verbose = true;
for img=1:numel(images)
image_orig = imread([root_dir images(img).name]);
% First attempt to use the Matlab one (fastest but not as accurate, if not present use yu et al.)
[bboxs, det_shapes] = detect_faces(image_orig, {'cascade', 'yu'});
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% Zhu and Ramanan and Yu et al. are slower, but also more accurate
% and can be used when vision toolbox is unavailable
% [bboxs, det_shapes] = detect_faces(image_orig, {'yu', 'zhu'});
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% The complete set that tries all three detectors starting with fastest
% and moving onto slower ones if fastest can't detect anything
% [bboxs, det_shapes] = detect_faces(image_orig, {'cascade', 'yu', 'zhu'});
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if(size(image_orig,3) == 3)
image = rgb2gray(image_orig);
end
%%
if(verbose)
f = figure;
if(max(image(:)) > 1)
imshow(double(image_orig)/255, 'Border', 'tight');
else
imshow(double(image_orig), 'Border', 'tight');
end
axis equal;
hold on;
end
for i=1:size(bboxs,2)
% Convert from the initial detected shape to CLM model parameters,
% if shape is available
bbox = bboxs(:,i);
if(~isempty(det_shapes))
shape = det_shapes(:,:,i);
inds = [1:60,62:64,66:68];
M = pdm.M([inds, inds+68, inds+68*2]);
E = pdm.E;
V = pdm.V([inds, inds+68, inds+68*2],:);
[ a, R, T, ~, params, err, shapeOrtho] = fit_PDM_ortho_proj_to_2D(M, E, V, shape);
g_param = [a; Rot2Euler(R)'; T];
l_param = params;
% Use the initial global and local params for clm fitting in the image
[shape,~,~,lhood,lmark_lhood,view_used] = Fitting_from_bb(image, [], bbox, pdm, patches, clmParams, 'gparam', g_param, 'lparam', l_param);
else
[shape,~,~,lhood,lmark_lhood,view_used] = Fitting_from_bb(image, [], bbox, pdm, patches, clmParams);
end
% shape correction for matlab format
shape = shape + 1;
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% Perform eye fitting now
shape_r_eye = zeros(numel(pdm_right_eye.M)/3, 2);
shape_r_eye(right_eye_inds_synth,:) = shape(right_eye_inds, :);
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[ a, R, T, ~, l_params] = fit_PDM_ortho_proj_to_2D(pdm_right_eye.M, pdm_right_eye.E, pdm_right_eye.V, shape_r_eye);
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bbox = [min(shape_r_eye(:,1)), min(shape_r_eye(:,2)), max(shape_r_eye(:,1)), max(shape_r_eye(:,2))];
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g_param = [a; Rot2Euler(R)'; T];
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[shape_r_eye] = Fitting_from_bb(image, [], bbox, pdm_right_eye, patches_right_eye, clmParams_eye, 'gparam', g_param, 'lparam', l_params);
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% Perform eye fitting now
shape_l_eye = zeros(numel(pdm_right_eye.M)/3, 2);
shape_l_eye(left_eye_inds_synth,:) = shape(left_eye_inds, :);
[ a, R, T, ~, l_params] = fit_PDM_ortho_proj_to_2D(pdm_left_eye.M, pdm_left_eye.E, pdm_left_eye.V, shape_l_eye);
bbox = [min(shape_l_eye(:,1)), min(shape_l_eye(:,2)), max(shape_l_eye(:,1)), max(shape_l_eye(:,2))];
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g_param = [a; Rot2Euler(R)'; T];
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[shape_l_eye] = Fitting_from_bb(image, [], bbox, pdm_left_eye, patches_left_eye, clmParams_eye, 'gparam', g_param, 'lparam', l_params);
plot(shape_l_eye(9:20,1), shape_l_eye(9:20,2), '.g', 'MarkerSize',7);
plot(shape_l_eye(1:8,1), shape_l_eye(1:8,2), '.b', 'MarkerSize',7);
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plot(shape_r_eye(9:20,1), shape_r_eye(9:20,2), '.g', 'MarkerSize',7);
plot(shape_r_eye(1:8,1), shape_r_eye(1:8,2), '.b', 'MarkerSize',7);
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end
hold off;
end