perform_farthest_point_sampling_mesh

function [points,D] = perform_farthest_point_sampling_mesh( vertex,faces, points, nbr_iter, options )

% perform_farthest_point_sampling - samples points using farthest seeding strategy
%
% [points,D] = perform_farthest_point_sampling_mesh( vertex,faces, points, nbr_iter, options );
%
%   points can be [] or can be a (nb.points,1) matrix of already computed 
%       sampling locations.
%
%   See also: perform_fast_marching_mesh.
%   
%   Copyright (c) 2007 Gabriel Peyre

options.null = 0;
if nargin<3
    nb_iter = 1;
end

[vertex,faces] = check_face_vertex(vertex,faces);

n = size(vertex,2);

L1 = getoptions(options, 'constraint_map', zeros(n,1) + Inf );

if nargin<2 || isempty(points)
    % initialize farthest points at random
    %points = round(rand(1,1)*(n-1))+1;
    points = 1;
    % replace by farthest point
    [points,L] = perform_farthest_point_sampling_mesh( vertex,faces, points, 1, options );
    points = points(end);
    nbr_iter = nbr_iter-1;
    L = min(zeros(n,1) + Inf, L1);
else
    % initial distance map
    L = min(zeros(n,1) + Inf, L1);
end
for i=1:nbr_iter
    if nbr_iter>5
        progressbar( i, nbr_iter );
    end
    options.nb_iter_max = Inf;
    options.constraint_map = L;
    D = my_eval_distance(vertex,faces, points(end), options);
    D = min(D,L); % known distance map to lanmarks
    L = min(D,L1); % cropp with other constraints
    % remove away data
    D(D==Inf) = 0;
    % compute farhtest points
    [tmp,I] = max(D(:));
    points = [points,I(1)];
end


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function D = my_eval_distance(vertex,faces,  x, options)

options.null = 0;

if length(x)>1
    D = zeros(n)+Inf;
    for i=1:length(x)
        D = min(D, my_eval_distance(vertex,faces,x(i)));
    end
    return;
end
[D,Z,Q] = perform_fast_marching_mesh(vertex, faces, x, options);