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 [OccluList BoundaryLaserOccluHori BoundaryLaserOccluVert]=LaserOccluLabel(k,nList); |
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40 | |
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41 | |
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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 batchSize NuRow_default SegVertYSize SegHoriXSize WeiBatchSize PopUpVertY PopUpHoriX taskName; |
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45 | |
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46 | BpWidthV = ceil(0.01*VertYNuDepth); |
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47 | BpWidthH = ceil(0.05*HoriXNuDepth); |
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48 | SE = strel('rectangle',[BpWidthV BpWidthH]); |
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49 | ThreVert = 0.5; |
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50 | ThreHori = 0.5; |
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51 | ThreFar = 15; |
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52 | % load data |
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53 | depthfile = strrep(filename{k},'img','depth_sph_corr'); % the depth filename |
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54 | load([ScratchDataFolder '/Gridlaserdata/' depthfile '.mat']); |
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55 | LaserDepth = Position3DGrid(:,:,4); |
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56 | |
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57 | load([ScratchDataFolder '/data/CleanSup/CleanSup' num2str(k) '.mat']); |
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58 | Sup = double(Sup); |
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59 | MaxSup = max( Sup(:)); |
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60 | MaskSky = Sup ==0; |
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61 | |
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62 | BoundaryPVert = conv2(Sup,[1 MaxSup],'valid').*( conv2(Sup,[1 -1],'valid') >0)... |
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63 | .* ~MaskSky(:,1:(end-1)) .* ~MaskSky(:,2:end); % two step build up hash index 1) Left > Righ index |
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64 | BoundaryPVert = BoundaryPVert + conv2(Sup,[MaxSup 1],'valid').* (conv2(Sup,[-1 1],'valid') >0)... |
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65 | .* ~MaskSky(:,1:(end-1)) .* ~MaskSky(:,2:end); % 2) Left < Righ index |
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66 | BoundaryPHori = conv2(Sup,[1; MaxSup],'valid').* (conv2(Sup,[1; -1],'valid') >0)... |
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67 | .* ~MaskSky(1:(end-1),:) .* ~MaskSky(2:end,:); % two step build up hash index 1) Top > bottom index |
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68 | BoundaryPHori = BoundaryPHori + conv2(Sup,[MaxSup; 1],'valid').*( conv2(Sup,[-1; 1],'valid') >0)... |
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69 | .* ~MaskSky(1:(end-1),:) .* ~MaskSky(2:end,:); % 2) Top < Bottom index |
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70 | |
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71 | % detect occlusion in both vertical and horizontal direction |
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72 | DiffDepthVert = abs(conv2(LaserDepth,[1; -1],'valid')); |
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73 | DiffDepthHori = abs(conv2(LaserDepth,[1 -1],'valid')); |
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74 | FraDiffDepthVert = DiffDepthVert./ sqrt(LaserDepth(1:(end-1),:) .* LaserDepth(2:end,:) ); |
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75 | %FraDiffDepthVert = DiffDepthVert./ min(LaserDepth(1:(end-1),:) , LaserDepth(2:end,:) ); |
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76 | OccFraDiffDepthVert = FraDiffDepthVert > ThreVert; |
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77 | OccFraDiffDepthVert(LaserDepth(1:(end-1),:) > ThreFar & LaserDepth(2:end,:) > ThreFar) = 0; |
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78 | FraDiffDepthHori = DiffDepthHori./ sqrt( LaserDepth(:,1:(end-1)) .* LaserDepth(:,2:end) ); |
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79 | %FraDiffDepthHori = DiffDepthHori./ min( LaserDepth(:,1:(end-1)) , LaserDepth(:,2:end) ); |
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80 | OccFraDiffDepthHori = FraDiffDepthHori > ThreHori; |
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81 | OccFraDiffDepthHori(LaserDepth(:,1:(end-1)) > ThreFar & LaserDepth(:,2:end) > ThreFar) = 0; |
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82 | |
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83 | BoundaryLaserOccluHori = (imdilate(OccFraDiffDepthVert, SE).*(BoundaryPHori ~= 0)); |
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84 | BoundaryLaserOccluVert = (imdilate(OccFraDiffDepthHori, SE).*(BoundaryPVert ~= 0)); |
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85 | OccluMap = zeros(size(LaserDepth)); |
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86 | OccluMap(:,1:(end-1)) = imdilate(OccFraDiffDepthHori, SE); |
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87 | OccluMap(1:(end-1),:) = imdilate(OccFraDiffDepthVert, SE); |
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88 | %figure(200);subplot(1,2,1); |
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89 | %figure; |
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90 | %disp('plot'); |
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91 | %Img = imresize(imread([GeneralDataFolder '/' ImgFolder '/' filename{k} ],'jpg'), [SegVertYSize SegHoriXSize]); |
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92 | %Img(:,:,1) = 255*imresize(OccluMap, [ SegVertYSize, SegHoriXSize]); |
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93 | %image(Img); |
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94 | |
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95 | OccluHash = setdiff(unique([BoundaryPHori(BoundaryLaserOccluHori ~= 0); BoundaryPVert(BoundaryLaserOccluVert ~= 0)]),0); |
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96 | List = nList(:,1)*MaxSup + nList(:,2); |
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97 | OccluList = false*ones(size(List)); |
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98 | if isempty(OccluHash) |
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99 | return; |
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100 | end |
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101 | mask = sum(repmat(List,[1 size(OccluHash,1)]) == repmat(OccluHash',[size(List,1) 1]),2) > 0; |
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102 | OccluList(mask) = true; |
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103 | return; |
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