[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 [FeaVector] = genFeaVector(f,fsup,VList,HList,i,near,NeighborFeaList);
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| 40 | %function [FeaVector] = genFeaVector(f,fsup,RowTop,RowBottom,ColumnLeft,ColumnRight,i,NeighborFeaList);
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| 41 | % This function set the feature to the right format of Feature Vector
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| 42 | global GeneralDataFolder ScratchDataFolder LocalFolder ClusterExecutionDirectory...
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| 43 | ImgFolder VertYNuPatch VertYNuDepth HoriXNuPatch HoriXNuDepth a_default b_default Ox_default Oy_default...
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| 44 | Horizon_default filename NuRow_default;
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| 45 |
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| 46 | if nargin < 7
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| 47 | NeighborFeaList = 1:5;
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| 48 | end
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| 49 |
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| 50 | NuRow = NuRow_default;
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| 51 |
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| 52 | % load pics info
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| 53 | PicsinfoName = strrep(filename{i},'img','picsinfo');
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| 54 | temp = dir([GeneralDataFolder '/PicsInfo/' PicsinfoName '.mat']);
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| 55 | if size(temp,1) == 0
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| 56 | a = a_default;
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| 57 | b = b_default;
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| 58 | Ox = Ox_default;
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| 59 | Oy = Oy_default;
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| 60 | Horizon = Horizon_default;
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| 61 | else
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| 62 | load([GeneralDataFolder '/PicsInfo/' PicsinfoName '.mat']);
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| 63 | end
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| 64 |
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| 65 | % generate the range of the row for the same thi (weight value)
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| 66 | %RowskyBottom = floor(NuRow/2);
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| 67 | %PatchSkyBottom = ceil(VertYNuDepth*(1-Horizon));
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| 68 | %if row <= RowskyBottom
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| 69 | % PatchRowRatio = PatchSkyBottom/RowskyBottom;
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| 70 | % RowTop = round((row-1)*PatchRowRatio+1);
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| 71 | % RowBottom = round(row*PatchRowRatio);
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| 72 | %else
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| 73 | % PatchRowRatio = (VertYNuDepth-PatchSkyBottom)/(NuRow-RowskyBottom);
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| 74 | % RowTop = round((row-RowskyBottom-1)*PatchRowRatio+1)+PatchSkyBottom;
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| 75 | % RowBottom = round((row-RowskyBottom)*PatchRowRatio)+PatchSkyBottom;
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| 76 | %end
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| 77 |
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| 78 | FeaVector = [];
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| 79 | % Superpixel Feature
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| 80 | if size(fsup,2)~=0
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| 81 | shift = [0 0; -1 0; 1 0; 0 -1; 0 1]; % left right top bottom
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| 82 | for l = 1:1
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| 83 | [Ix Iy] = meshgrid(max(min(HList+shift(l,1),HoriXNuDepth),1),...
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| 84 | max(min(VList+shift(l,2),VertYNuDepth),1));
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| 85 | maskNeibor = sub2ind([VertYNuDepth, HoriXNuDepth], Iy(:), Ix(:));
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| 86 | if (sum(sum(Iy==1))== size(Iy(:),1) && l ==4) || (sum(sum( Iy == VertYNuDepth ))== size(Iy(:),1) && l ==5)
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| 87 | FeaVector =[ FeaVector ;(conv2(fsup(:,f(maskNeibor,1)),[0.25; 0.25; 0.25; 0.25],'same'))];
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| 88 | else
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| 89 | FeaVector =[ FeaVector ;fsup(:,f(maskNeibor,1))];
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| 90 | end
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| 91 | end
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| 92 | end
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| 93 | % Hi Resolution
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| 94 | shift = [0 0; -1 0; 1 0; 0 -1; 0 1];
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| 95 |
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| 96 | for l = NeighborFeaList
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| 97 | [Ix Iy] = meshgrid(max(min(HList+shift(l,1),HoriXNuDepth),1),...
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| 98 | max(min(VList+shift(l,2),VertYNuDepth),1));
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| 99 | maskNeibor = sub2ind([VertYNuDepth, HoriXNuDepth], Iy(:), Ix(:));
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| 100 | if (sum(sum(Iy==1))== size(Iy(:),1) && l ==4)||(sum(sum( Iy == VertYNuDepth ))== size(Iy(:),1) && l ==5)
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| 101 | FeaVector =[ FeaVector ;(conv2(f(maskNeibor,2:35),[0.25; 0.25; 0.25; 0.25],'same'))'];
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| 102 | else
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| 103 | FeaVector =[ FeaVector ;f(maskNeibor,2:35)'];
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| 104 | end
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| 105 | end
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| 106 |
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| 107 | % Med 1/3 Resolution
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| 108 | if near ~=1
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| 109 | shift = 3*[0 0; -1 0; 1 0; 0 -1; 0 1];
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| 110 | end
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| 111 | for l = NeighborFeaList
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| 112 | [Ix Iy] = meshgrid(max(min(HList+shift(l,1),HoriXNuDepth),1),...
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| 113 | max(min(VList+shift(l,2),VertYNuDepth),1));
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| 114 | maskNeibor = sub2ind([VertYNuDepth, HoriXNuDepth], Iy(:), Ix(:));
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| 115 | if (sum(sum(Iy==1))== size(Iy(:),1) && l ==4)||(sum(sum( Iy == VertYNuDepth ))== size(Iy(:),1) && l ==5)
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| 116 | FeaVector =[ FeaVector ;(conv2(f(maskNeibor,36:69),[0.25; 0.25; 0.25; 0.25],'same'))'];
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| 117 | else
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| 118 | FeaVector =[ FeaVector ;f(maskNeibor,36:69)'];
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| 119 | end
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| 120 | end
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| 121 |
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| 122 | % Low 1/9 REsolution
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| 123 | if near ~=1
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| 124 | shift = 9*[0 0; -1 0; 1 0; 0 -1; 0 1];
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| 125 | end
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| 126 | for l = NeighborFeaList
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| 127 | [Ix Iy] = meshgrid(max(min(HList+shift(l,1),HoriXNuDepth),1),...
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| 128 | max(min(VList+shift(l,2),VertYNuDepth),1));
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| 129 | maskNeibor = sub2ind([VertYNuDepth, HoriXNuDepth], Iy(:), Ix(:));
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| 130 | if (sum(sum(Iy==1))== size(Iy(:),1) && l ==4)||(sum(sum( Iy == VertYNuDepth ))== size(Iy(:),1) && l ==5)
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| 131 | FeaVector =[ FeaVector ;(conv2(f(maskNeibor,70:103),[0.25; 0.25; 0.25; 0.25],'same'))'];
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| 132 | else
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| 133 | FeaVector =[ FeaVector ;f(maskNeibor,70:103)'];
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| 134 | end
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| 135 | end
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| 136 |
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| 137 | % other features
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| 138 | shift = [0 0];%; -1 0; 1 0; 0 -1; 0 1];
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| 139 | for l = 1:1
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| 140 | [Ix Iy] = meshgrid(max(min(HList+shift(l,1),HoriXNuDepth),1),...
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| 141 | max(min(VList+shift(l,2),VertYNuDepth),1));
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| 142 | maskNeibor = sub2ind([VertYNuDepth, HoriXNuDepth], Iy(:), Ix(:));
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| 143 | %if (sum(sum(Iy==1))== size(Iy(:),1) && l ==4)||(sum(sum( Iy == VertYNuDepth ))== size(Iy(:),1) && l ==5)
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| 144 | % maskNeibor2 = sub2ind([VertYNuDepth, HoriXNuDepth], Iy(:)+1, Ix(:));
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| 145 | % FeaVector =[ FeaVector ;(f(maskNeibor,104)+f(maskNeibor2,104))'/2];
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| 146 | %else
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| 147 | FeaVector =[ FeaVector ;f(maskNeibor,104)'];
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| 148 | %end
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| 149 | end
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| 150 |
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