1 | %=======================================================================
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2 | % Copyright 2008-2014, LEGI UMR 5519 / CNRS UJF G-INP, Grenoble, France
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3 | % http://www.legi.grenoble-inp.fr
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4 | % Joel.Sommeria - Joel.Sommeria (A) legi.cnrs.fr
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5 | %
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6 | % This file is part of the toolbox UVMAT.
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7 | %
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8 | % UVMAT is free software; you can redistribute it and/or modify
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9 | % it under the terms of the GNU General Public License as published
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10 | % by the Free Software Foundation; either version 2 of the license,
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11 | % or (at your option) any later version.
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12 | %
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13 | % UVMAT is distributed in the hope that it will be useful,
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14 | % but WITHOUT ANY WARRANTY; without even the implied warranty of
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15 | % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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16 | % GNU General Public License (see LICENSE.txt) for more details.
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17 | %=======================================================================
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18 |
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19 | function [H,Hnorm,inv_Hnorm] = compute_homography(m,M);
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20 |
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21 | %compute_homography
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22 | %
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23 | %[H,Hnorm,inv_Hnorm] = compute_homography(m,M)
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24 | %
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25 | %Computes the planar homography between the point coordinates on the plane (M) and the image
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26 | %point coordinates (m).
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27 | %
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28 | %INPUT: m: homogeneous coordinates in the image plane (3xN matrix)
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29 | % M: homogeneous coordinates in the plane in 3D (3xN matrix)
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30 | %
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31 | %OUTPUT: H: Homography matrix (3x3 homogeneous matrix)
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32 | % Hnorm: Normalization matrix used on the points before homography computation
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33 | % (useful for numerical stability is points in pixel coordinates)
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34 | % inv_Hnorm: The inverse of Hnorm
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35 | %
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36 | %Definition: m ~ H*M where "~" means equal up to a non zero scalar factor.
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37 | %
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38 | %Method: First computes an initial guess for the homography through quasi-linear method.
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39 | % Then, if the total number of points is larger than 4, optimize the solution by minimizing
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40 | % the reprojection error (in the least squares sense).
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41 | %
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42 | %
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43 | %Important functions called within that program:
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44 | %
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45 | %comp_distortion_oulu: Undistorts pixel coordinates.
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46 | %
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47 | %compute_homography.m: Computes the planar homography between points on the grid in 3D, and the image plane.
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48 | %
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49 | %project_points.m: Computes the 2D image projections of a set of 3D points, and also returns te Jacobian
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50 | % matrix (derivative with respect to the intrinsic and extrinsic parameters).
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51 | % This function is called within the minimization loop.
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52 |
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53 |
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54 |
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55 |
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56 | Np = size(m,2);
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57 |
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58 | if size(m,1)<3,
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59 | m = [m;ones(1,Np)];
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60 | end;
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61 |
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62 | if size(M,1)<3,
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63 | M = [M;ones(1,Np)];
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64 | end;
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65 |
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66 |
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67 | m = m ./ (ones(3,1)*m(3,:));
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68 | M = M ./ (ones(3,1)*M(3,:));
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69 |
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70 | % Prenormalization of point coordinates (very important):
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71 | % (Affine normalization)
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72 |
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73 | ax = m(1,:);
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74 | ay = m(2,:);
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75 |
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76 | mxx = mean(ax);
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77 | myy = mean(ay);
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78 | ax = ax - mxx;
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79 | ay = ay - myy;
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80 |
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81 | scxx = mean(abs(ax));
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82 | scyy = mean(abs(ay));
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83 |
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84 |
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85 | Hnorm = [1/scxx 0 -mxx/scxx;0 1/scyy -myy/scyy;0 0 1];
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86 | inv_Hnorm = [scxx 0 mxx ; 0 scyy myy; 0 0 1];
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87 |
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88 | mn = Hnorm*m;
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89 |
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90 | % Compute the homography between m and mn:
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91 |
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92 | % Build the matrix:
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93 |
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94 | L = zeros(2*Np,9);
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95 |
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96 | L(1:2:2*Np,1:3) = M';
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97 | L(2:2:2*Np,4:6) = M';
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98 | L(1:2:2*Np,7:9) = -((ones(3,1)*mn(1,:)).* M)';
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99 | L(2:2:2*Np,7:9) = -((ones(3,1)*mn(2,:)).* M)';
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100 |
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101 | if Np > 4,
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102 | L = L'*L;
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103 | end;
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104 |
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105 | [U,S,V] = svd(L);
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106 |
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107 | hh = V(:,9);
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108 | hh = hh/hh(9);
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109 |
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110 | Hrem = reshape(hh,3,3)';
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111 | %Hrem = Hrem / Hrem(3,3);
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112 |
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113 |
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114 | % Final homography:
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115 |
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116 | H = inv_Hnorm*Hrem;
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117 |
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118 | if 0,
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119 | m2 = H*M;
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120 | m2 = [m2(1,:)./m2(3,:) ; m2(2,:)./m2(3,:)];
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121 | merr = m(1:2,:) - m2;
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122 | end;
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123 |
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124 | %keyboard;
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125 |
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126 | %%% Homography refinement if there are more than 4 points:
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127 |
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128 | if Np > 4,
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129 |
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130 | % Final refinement:
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131 | hhv = reshape(H',9,1);
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132 | hhv = hhv(1:8);
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133 |
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134 | for iter=1:10,
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135 |
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136 |
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137 |
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138 | mrep = H * M;
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139 |
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140 | J = zeros(2*Np,8);
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141 |
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142 | MMM = (M ./ (ones(3,1)*mrep(3,:)));
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143 |
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144 | J(1:2:2*Np,1:3) = -MMM';
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145 | J(2:2:2*Np,4:6) = -MMM';
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146 |
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147 | mrep = mrep ./ (ones(3,1)*mrep(3,:));
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148 |
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149 | m_err = m(1:2,:) - mrep(1:2,:);
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150 | m_err = m_err(:);
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151 |
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152 | MMM2 = (ones(3,1)*mrep(1,:)) .* MMM;
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153 | MMM3 = (ones(3,1)*mrep(2,:)) .* MMM;
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154 |
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155 | J(1:2:2*Np,7:8) = MMM2(1:2,:)';
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156 | J(2:2:2*Np,7:8) = MMM3(1:2,:)';
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157 |
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158 | MMM = (M ./ (ones(3,1)*mrep(3,:)))';
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159 |
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160 | hh_innov = inv(J'*J)*J'*m_err;
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161 |
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162 | hhv_up = hhv - hh_innov;
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163 |
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164 | H_up = reshape([hhv_up;1],3,3)';
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165 |
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166 | %norm(m_err)
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167 | %norm(hh_innov)
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168 |
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169 | hhv = hhv_up;
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170 | H = H_up;
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171 |
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172 | end;
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173 |
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174 |
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175 | end;
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176 |
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177 | if 0,
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178 | m2 = H*M;
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179 | m2 = [m2(1,:)./m2(3,:) ; m2(2,:)./m2(3,:)];
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180 | merr = m(1:2,:) - m2;
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181 | end;
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182 |
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183 | return;
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184 |
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185 | %test of Jacobian
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186 |
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187 | mrep = H*M;
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188 | mrep = mrep ./ (ones(3,1)*mrep(3,:));
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189 |
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190 | m_err = mrep(1:2,:) - m(1:2,:);
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191 | figure(8);
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192 | plot(m_err(1,:),m_err(2,:),'r+');
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193 | std(m_err')
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