[37] | 1 | % * This code was used in the following articles:
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| 2 | % * [1] Learning 3-D Scene Structure from a Single Still Image,
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| 3 | % * Ashutosh Saxena, Min Sun, Andrew Y. Ng,
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| 4 | % * In ICCV workshop on 3D Representation for Recognition (3dRR-07), 2007.
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| 5 | % * (best paper)
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| 6 | % * [2] 3-D Reconstruction from Sparse Views using Monocular Vision,
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| 7 | % * Ashutosh Saxena, Min Sun, Andrew Y. Ng,
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| 8 | % * In ICCV workshop on Virtual Representations and Modeling
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| 9 | % * of Large-scale environments (VRML), 2007.
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| 10 | % * [3] 3-D Depth Reconstruction from a Single Still Image,
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| 11 | % * Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng.
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| 12 | % * International Journal of Computer Vision (IJCV), Aug 2007.
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| 13 | % * [6] Learning Depth from Single Monocular Images,
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| 14 | % * Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng.
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| 15 | % * In Neural Information Processing Systems (NIPS) 18, 2005.
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| 16 | % *
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| 17 | % * These articles are available at:
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| 18 | % * http://make3d.stanford.edu/publications
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| 19 | % *
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| 20 | % * We request that you cite the papers [1], [3] and [6] in any of
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| 21 | % * your reports that uses this code.
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| 22 | % * Further, if you use the code in image3dstiching/ (multiple image version),
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| 23 | % * then please cite [2].
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| 24 | % *
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| 25 | % * If you use the code in third_party/, then PLEASE CITE and follow the
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| 26 | % * LICENSE OF THE CORRESPONDING THIRD PARTY CODE.
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| 27 | % *
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| 28 | % * Finally, this code is for non-commercial use only. For further
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| 29 | % * information and to obtain a copy of the license, see
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| 30 | % *
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| 31 | % * http://make3d.stanford.edu/publications/code
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| 32 | % *
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| 33 | % * Also, the software distributed under the License is distributed on an
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| 34 | % * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
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| 35 | % * express or implied. See the License for the specific language governing
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| 36 | % * permissions and limitations under the License.
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| 37 | % *
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| 38 | % */
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| 39 | function [ X, Y, Scale, Coeff, Coeffs ] = FindTarget( defaultPara, Field, Target, Field_top, Field_left, target_center_topOffset, target_center_leftOffset, ...
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| 40 | NormalizedEpipoalLine, ImgScale, ScaleFactors, TargetFullyInField, EnableEpipolarLineFlag)
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| 41 |
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| 42 | % [ X, Y, Scale, Coeff, Coeffs ] = FindTarget( Field, Target, Field_top, Field_left, NormalizedEpipoalLine, ...
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| 43 | % ImgScale, ScaleFactors, TargetFullyInField, EnableEpipolarLineFlag)
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| 44 |
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| 45 | % Search for Target image in Field image (gray) at multiple different
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| 46 | % Target sizes (scale factors).
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| 47 | % Field - Image being searched
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| 48 | % Target - Image being Sought
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| 49 | % ScaleFactors - Vector of scale factors for Target, target is scaled
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| 50 | % by each of these factors (linear ie # lines in target =
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| 51 | % old_target_lies * ScaleFactor)
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| 52 | % TargetFullyInField - Set to True if you are CERTAIN that the Target
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| 53 | % is fully in the Field. Helps ignore spurrious correlations, but
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| 54 | % will prevent finding location of Target that is only partially in
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| 55 | % Field. True Should be faster, but isn't appreciably.. sigh....
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| 56 |
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| 57 | % local_field = histeq(Field); % should not to histogram equalization in such a small region
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| 58 |
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| 59 | EpipolarThre = 0.05;% used 0.05
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| 60 | num_scales = size( ScaleFactors, 2 );
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| 61 | best_max = 0.0;
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| 62 | best_id = [];
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| 63 | Coeffs = [];
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| 64 |
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| 65 | for scale_id = 1:num_scales
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| 66 | current_scale = ScaleFactors( scale_id );
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| 67 | target_tmp = imresize(Target, current_scale, 'bicubic');
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| 68 | % disp('Scaling the target accordingly');
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| 69 | top = size(target_tmp,1);
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| 70 | left = size(target_tmp,2);
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| 71 | target_tmp_center_topOffset = target_center_topOffset*current_scale;
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| 72 | target_tmp_center_leftOffset = target_center_leftOffset*current_scale;
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| 73 | adj_row = size(target_tmp, 1 ) - 1;
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| 74 | adj_col = size(target_tmp, 2 ) - 1;
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| 75 |
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| 76 | % Note normxcorr2 barfs if Target > Field, so skip iteration if
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| 77 | % target is scaled too big.
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| 78 | if ( (size(target_tmp, 1 ) <= size(Field,1)) && (size(target_tmp, 2 ) <= size(Field,2)) ) % Field is always bigger than Target
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| 79 |
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| 80 | % This is where the Heavy lifting is done. Find norimalzied
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| 81 | % covaraince at all offsets between target and field
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| 82 | % (including partial overlaps)
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| 83 | if defaultPara.Flag.UseNormXCorr2 == 1
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| 84 | res = normxcorr2( target_tmp, Field );
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| 85 | elseif defaultPara.Flag.UseNormXCorr2 == 0
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| 86 | res = xcorr2( target_tmp, Field );
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| 87 | elseif defaultPara.Flag.UseNormXCorr2 == 2
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| 88 | res = normxcorr2_mex( target_tmp, Field );
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| 89 | end
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| 90 |
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| 91 | % When we KNOW the target is completely within the field, trim
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| 92 | % correlations that incldue partial overlaps, this reduces
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| 93 | % false positives.
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| 94 | if (TargetFullyInField)
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| 95 | % If we know that the target is compeltely within the field,
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| 96 | % exclude portions of the correlation that are generated by
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| 97 | % only a partial overlap of the target and field.
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| 98 | height = size(Field,1) - size(target_tmp,1) + 1;
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| 99 | width = size(Field,2) - size(target_tmp,2) + 1;
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| 100 | clear target_tmp;
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| 101 | % use only those results where the Target is compeltely
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| 102 | % inside the Field.
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| 103 | res = res( top:(top+height-1), left:(left+width-1) );
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| 104 | adj_row = 0;
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| 105 | adj_col = 0;
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| 106 | end
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| 107 |
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| 108 | if EnableEpipolarLineFlag
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| 109 | Xim = [ Field_left + reshape(repmat( 1:size(res,2), size(res,1),1) ,1, []) - adj_col;...
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| 110 | Field_top + reshape(repmat( 1:size(res,1)', 1, size(res,2)) ,1, []) - adj_row];
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| 111 | Residual = abs( NormalizedEpipoalLine' * [ Xim(1:2,:); ones(1, size(Xim(1:2,:),2))]);
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| 112 | Mask = Residual <= EpipolarThre*max(ImgScale);
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| 113 | res( ~reshape(Mask, size(res,1), [])) = 0; % set to the lowest possible corrolation value
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| 114 | end
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| 115 | % Max(matrix) returns the largest value in each col, in a row vector
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| 116 | % [ max_vals, max_row_inds ] = max( abs( res ) );
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| 117 | % Find the Col with the bigest Max
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| 118 | % [ max_val , max_col_ind ] = max( max_vals );
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| 119 | % Get the row & col with the largest correlation
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| 120 | % max_row_ind = max_row_inds( max_col_ind );
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| 121 | % Adjust to get offset of scaled Target, in field, in units of
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| 122 | % FIELD pixels.
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| 123 | if all(res == 0)
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| 124 | % disp('Res is all not close enough to Epipolar line');
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| 125 | continue;
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| 126 | end
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| 127 | % disp('Size of Res =');
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| 128 | % size(res)
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| 129 | [xymax,smax,xymin,smin] = extrema2(abs(res));
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| 130 | [ Vsort Isort]= sort(xymax,'descend');
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| 131 |
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| 132 | if size(Isort,1) >=2
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| 133 | [row_ind col_ind] = ind2sub(size(res),smax(Isort(1:2)));
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| 134 | elseif size(Isort,1) == 0
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| 135 | continue;
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| 136 | else
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| 137 | % disp('No other Similiar Point');
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| 138 | [row_ind col_ind] = ind2sub(size(res),smax(Isort(1)));
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| 139 | end
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| 140 |
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| 141 | Coeffs( scale_id ).index = scale_id;
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| 142 | Coeffs( scale_id ).targetScale = current_scale;
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| 143 | Coeffs( scale_id ).offsetRow = row_ind(1) - adj_row + target_tmp_center_topOffset;
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| 144 | Coeffs( scale_id ).offsetCol = col_ind(1) - adj_col + target_tmp_center_leftOffset;
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| 145 | Coeffs( scale_id ).correlation = Vsort(1);
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| 146 |
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| 147 | if size(Isort,1) >=2
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| 148 | Coeffs( scale_id ).SecondCorrelation = Vsort(2);
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| 149 | else
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| 150 | % disp('No other Similiar Point');
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| 151 | Coeffs( scale_id ).SecondCorrelation = 0;
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| 152 | end
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| 153 | % Coeffs( scale_id ).offsetRow = max_row_ind - adj_row + target_tmp_center_topOffset;
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| 154 | % Coeffs( scale_id ).offsetCol = max_col_ind - adj_col + target_tmp_center_leftOffset;
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| 155 | % Coeffs( scale_id ).correlation = max_val;
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| 156 |
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| 157 | if (( scale_id==1) || (Vsort(1) > best_max) )
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| 158 | best_max = Vsort(1);
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| 159 | best_id = scale_id;
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| 160 | end % check for new best location among different Scale
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| 161 |
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| 162 | end % make sure target <= Field
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| 163 |
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| 164 | end % loop over all scaled
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| 165 |
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| 166 | if ~isempty(best_id)
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| 167 | X = Coeffs( best_id ).offsetCol;
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| 168 | Y = Coeffs( best_id ).offsetRow;
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| 169 | Scale = Coeffs( best_id ).targetScale;
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| 170 | Coeff = [ Coeffs( best_id ).correlation; Coeffs( best_id ).SecondCorrelation];
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| 171 | else
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| 172 | X = 0;
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| 173 | Y = 0;
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| 174 | Scale = 1;
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| 175 | Coeff = [0; 0];
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| 176 | end
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| 177 |
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| 178 | return %end function
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