[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 [Pocclu] = ClosetOcclusion(defaultPara, ScaleImg, Pair, ModelInfoTarget, TargetPointPix, INDTarget, ModelInfoField, FieldPointPix, INDField) |
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| 40 | % function return the closest occlusion point on specific ray TargetPointPix |
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| 41 | |
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| 42 | % ========================================== |
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| 43 | |
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| 44 | % PlaneParaMeter Scaling and Transform to Target viewpoint |
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| 45 | PlaneParaField = ModelInfoField.Model.PlaneParaInfo.PlanePara; |
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| 46 | PlaneParaField = PlaneParaField( :,ModelInfoField.Model.PlaneParaInfo.Sup2Para(ModelInfoField.Model.PlaneParaInfo.SupEpand(INDField))); |
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| 47 | PlaneParaField2Target = PlaneParaField'*Pair.R./repmat(1-PlaneParaField'*Pair.T,1,3); % (n by 3 |
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| 48 | |
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| 49 | |
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| 50 | % Find intersection with ray and the PlaneParaMeter |
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| 51 | OccluDepthTarget = 1./(PlaneParaField2Target*ModelInfoTarget.Model.Ray(:,INDTarget))'; % (3 by n) |
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| 52 | InterSectP = repmat(ModelInfoTarget.Model.Ray(:,INDTarget),1,length( OccluDepthTarget)).*repmat(OccluDepthTarget,3,1); |
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| 53 | |
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| 54 | % Reproj the intersect point to Field viewpoint, check if in the superpixel that planes belong to |
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| 55 | NumINDField = length( INDField); |
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| 56 | ReProjField = defaultPara.InrinsicK1*(Pair.R*InterSectP + repmat( Pair.T, 1,NumINDField)); |
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| 57 | ReProjField = ReProjField(1:2,:)./repmat( ReProjField(3,:),2,1); |
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| 58 | ScaleDepth = size(ModelInfoTarget.Model.Depth.FitDepth); |
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| 59 | [ ReProjFieldIND] = ProjPosi2Mask( ScaleImg, ScaleDepth, ReProjField); |
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| 60 | OccluMark = ModelInfoField.Model.Sup(ReProjFieldIND) == ModelInfoField.Model.Sup(INDField); |
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| 61 | |
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| 62 | |
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| 63 | % find the closest occlued point |
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| 64 | OccluDepthTarget = OccluDepthTarget(OccluMark); |
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| 65 | [V I ]= min(OccluDepthTarget); |
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| 66 | Pocclu=ReProjField(:,OccluMark); |
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| 67 | Pocclu = Pocclu(:,I); |
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| 68 | |
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| 69 | if V > ModelInfoTarget.Model.PlaneParaInfo.FitDepth(INDTarget) |
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| 70 | Pocclu = []; |
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| 71 | end |
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| 72 | |
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| 73 | return; |
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| 74 | |
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| 75 | |
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