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main_ordinary_3d_time.m
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% this toolbox is an addition to the toolbox provided by the authors of
% CEPPnP and OPnP
% we extended it to show the use of MLPnP
% if you use this file it would be neat to cite our paper:
%
% @INPROCEEDINGS {mlpnp2016,
% author = "Urban, S.; Leitloff, J.; Hinz, S.",
% title = "MLPNP - A REAL-TIME MAXIMUM LIKELIHOOD SOLUTION TO THE PERSPECTIVE-N-POINT PROBLEM.",
% booktitle = "ISPRS Annals of Photogrammetry, Remote Sensing \& Spatial Information Sciences",
% year = "2016",
% volume = "3",
% pages = "131-138"}
%
% Copyright (C) <2016> <Steffen Urban>
% Steffen Urban email: [email protected]
% Copyright (C) 2016 Steffen Urban
%
% This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License along
% with this program; if not, write to the Free Software Foundation, Inc.,
% 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 28.06.2016 Steffen Urban
clear; clc;
IniToolbox;
% experimental parameters
nl= [1,2,3,4,5,6,7,8,9,10];
nlsamples = [0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1]; %percentatge of samples for each sigma
npts= [10,100:100:2000];
num = 10;
% compared methods
A= zeros(size(npts));
B= zeros(num,1);
% if you want to use UPnP you have to download and install OpenGV
% also if you want to reproduce the runtime shown in the MLPnP paper
% yout have to install the OpenGV fork with MLPnP
name = {'MLPnPWithCov','MLPnP','LHM', 'EPnP+GN', 'RPnP', 'DLS', 'PPnP', 'ASPnP', 'SDP','OPnP', 'EPPnP', 'CEPPnP'};
f = {@MLPNP_with_COV, @MLPNP_without_COV,@LHM, @EPnP_GN, @RPnP, @robust_dls_pnp, @PPnP, @ASPnP, @GOP, @OPnP, @EPPnP, @CEPPnP};
marker = { 'x', 'd', 's', 'd', '^', '*', '<', 'v', '>','o','+','<'};
color = {'g', 'g', 'c', [1,0.5,0],'m', [1,0.5,1], 'b', 'y', 'r','k','k',[1,0.5,0.5]};
markerfacecolor = {'g','b','c',[1,0.5,0],'m', [1,0.5,1], 'b', 'y', 'r','k','n',[0,0.5,0.5]};
%
method_list= struct('name', name, 'f', f, 'mean_r', A, 'mean_t', A,...
'med_r', A, 'med_t', A, 'std_r', A, 'std_t', A, 'r', B, 't', B,...
'marker', marker, 'color', color, 'markerfacecolor', markerfacecolor);
% experiments
for i= 1:length(npts)
npt= npts(i);
fprintf('npt = %d (num sg = %d ): ', npt, length(nl));
for k= 1:length(method_list)
method_list(k).c = zeros(1,num);
method_list(k).e = zeros(1,num);
method_list(k).r = zeros(1,num);
method_list(k).t = zeros(1,num);
end
%index_fail = [];
index_fail = cell(1,length(name));
XXw = zeros(3,npts(i),num);
xxn = zeros(2,npts(i),num);
cov = zeros(9,npts(i),num);
v = zeros(3,npts(i),num);
for j= 1:num
% camera's parameters
width = 640;
height = 480;
f = 800;
K = [f 0 0
0 f 0
0 0 1];
% generate 3d coordinates in camera space
Xc= [xrand(1,npt,[-2 2]); xrand(1,npt,[-2 2]); xrand(1,npt,[4 8])];
t= mean(Xc,2);
R= rodrigues(randn(3,1));
XXw(:,:,j)= inv(R)*(Xc-repmat(t,1,npt));
% projection
xx= [Xc(1,:)./Xc(3,:); Xc(2,:)./Xc(3,:)]*f;
randomvals = randn(2,npt);
nnl = round(npt * nlsamples);
nls = zeros(1,npt);
id = 1;
for idnl = 1:length(nl)
sigma = nl(idnl);
nls(id:id+nnl(idnl)-1) = sigma .* ones(1,nnl(idnl));
id = id+nnl(idnl);
end
xxn(:,:,j)= xx+randomvals.*[nls;nls];
homx = [xxn(:,:,j)/f; ones(1,size(xxn(:,:,j),2))];
v(:,:,j) = normc(homx);
Cu = zeros(2,2,length(nls));
Evv = zeros(3,3,length(nls));
for id = 1:length(nls);
Cu(:,:,id) = [nls(id) 0; 0 nls(id)];
%cov(:,id) = reshape(Cu(:,:,id),4,1);
J = (eye(3)-(v(:,id,j)*v(:,id,j)')/(v(:,id,j)'*v(:,id,j)))/norm(homx(:,id));
Evv(:,:,id) = J*[Cu(:,:,id) [0;0]; 0 0 1]*J';
cov(:,id,j) = reshape(Evv(:,:,id),9,1);
end
end
% pose estimation
for k= 1:length(method_list)
tic;
for j=1:num
try
if strcmp(method_list(k).name, 'CEPPnP')
[R1,t1]= method_list(k).f(XXw(:,:,j),xxn(:,:,j)/f,Cu);
elseif strcmp(method_list(k).name, 'MLPnP') || ...
strcmp(method_list(k).name, 'MLPnPWithCov')
[R1,t1]= method_list(k).f(XXw(:,:,j),v(:,:,j),cov(:,:,j));
else
[R1,t1]= method_list(k).f(XXw(:,:,j),xxn(:,:,j)/f);
end
catch
end
end
tcost = toc;
method_list(k).mean_c(i)= tcost * 1000/num;
meanTime(i,k+1) = method_list(k).mean_c(i);
meanTime(i,1) = npts(i);
showpercent(k,length(method_list));
end
fprintf('\n');
end
save ordinary3DresultsTime method_list npts;
plotOrdinary3DTime;