80 lines
2.4 KiB
Mathematica
80 lines
2.4 KiB
Mathematica
|
clear
|
||
|
|
addpath('../PDM_helpers/');
|
||
|
|
addpath(genpath('../fitting/'));
|
||
|
|
addpath('../models/');
|
||
|
|
addpath(genpath('../face_detection'));
|
||
|
|
addpath('../CCNF/');
|
||
|
|
|
||
|
|
%% loading the patch experts
|
||
|
|
|
||
|
|
[clmParams, pdm] = Load_CLM_params_66();
|
||
|
|
|
||
|
|
% A CLM-Z model trained on Multi-PIE and BU-4DFE
|
||
|
|
[patches] = Load_Patch_Experts( '../models/clmz/', 'svr_patches_multi_pie_*.mat', '../models/clmz/', 'svr_depth_patches_*.mat', clmParams);
|
||
|
|
|
||
|
|
clmParams.multi_modal_types = patches(1).multi_modal_types;
|
||
|
|
|
||
|
|
%%
|
||
|
|
|
||
|
|
images = {'sample_depth_imgs/1.jpg', 'sample_depth_imgs/2.jpg', 'sample_depth_imgs/3.jpg', 'sample_depth_imgs/4.jpg', 'sample_depth_imgs/5.jpg'};
|
||
|
|
images_depth = {'sample_depth_imgs/1d.png', 'sample_depth_imgs/2d.png', 'sample_depth_imgs/3d.png', 'sample_depth_imgs/4d.png', 'sample_depth_imgs/5d.png'};
|
||
|
|
verbose = true;
|
||
|
|
|
||
|
|
for img=1:numel(images)
|
||
|
|
|
||
|
|
image_orig = imread(images{img});
|
||
|
|
|
||
|
|
image_depth = imread(images_depth{img});
|
||
|
|
|
||
|
|
% Need to convert from the disparity to depth values, and threshold
|
||
|
|
image_depth = 10000./(image_depth);
|
||
|
|
image_depth(image_depth > 300) = 0;
|
||
|
|
|
||
|
|
% First attempt to use the Matlab one (fastest but not as accurate, if not present use yu et al.)
|
||
|
|
[bboxs] = detect_faces(image_orig, {'cascade', 'zhu'});
|
||
|
|
|
||
|
|
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
|
||
|
|
bbox = bboxs(:,i);
|
||
|
|
|
||
|
|
% Use the initial global and local params for clm fitting in the image
|
||
|
|
[shape,~,~,lhood,lmark_lhood,view_used] = Fitting_from_bb(image, image_depth, bbox, pdm, patches, clmParams);
|
||
|
|
|
||
|
|
% shape correction for matlab format
|
||
|
|
shape = shape + 1;
|
||
|
|
|
||
|
|
if(verbose)
|
||
|
|
|
||
|
|
% valid points to draw (not to draw self-occluded ones)
|
||
|
|
v_points = logical(patches(1).visibilities(view_used,:));
|
||
|
|
|
||
|
|
try
|
||
|
|
plot(shape(v_points,1), shape(v_points',2),'.r','MarkerSize',20);
|
||
|
|
plot(shape(v_points,1), shape(v_points',2),'.b','MarkerSize',10);
|
||
|
|
catch warn
|
||
|
|
|
||
|
|
end
|
||
|
|
end
|
||
|
|
|
||
|
|
end
|
||
|
|
hold off;
|
||
|
|
|
||
|
|
end
|