sustaining_gazes/matlab_version/face_validation/face_check_preloaded.m

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2016-04-28 21:40:36 +02:00
function [ decision ] = face_check_preloaded( img, shape, global_params, faceCheckers )
%FACE_CHECK_WILD Summary of this function goes here
% Detailed explanation goes here
if(size(img,3) == 3)
img = rgb2gray(img);
end
% first need to determine the view
centres = cat(1, faceCheckers.centres);
dists = centres*pi/180 - repmat(global_params(2:4)',size(centres,1),1);
[~,view_id] = min(sum(dists.^2,2));
img_crop = Crop(img, shape, faceCheckers(view_id).triangulation,...
faceCheckers(view_id).triX, faceCheckers(view_id).mask,...
faceCheckers(view_id).alphas, faceCheckers(view_id).betas,...
faceCheckers(view_id).nPix, faceCheckers(view_id).minX, ...
faceCheckers(view_id).minY);
img_crop = reshape(img_crop(logical(faceCheckers(view_id).mask)), 1, faceCheckers(view_id).nPix);
img_crop(isnan(img_crop)) = 0;
% normalisation (local)
img_crop = (img_crop - mean(img_crop));
norms = std(img_crop);
if(norms==0)
norms = 1;
end
img_crop = img_crop / norms;
% Projection onto principal components
% normalisation (global)
img_crop = img_crop - faceCheckers(view_id).mean_ex;
img_crop = img_crop ./ faceCheckers(view_id).std_ex;
img_crop = img_crop * faceCheckers(view_id).principal_components;
decision = faceCheckers(view_id).b + faceCheckers(view_id).w' * img_crop';
% normalise decision from ~ -1, 1 to [0,3]
decision = (decision + 1) * 1.5;