[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 [ Rc1_2 ConS1_2 RoughConS1_2 tempConS1_2] = EndPoint2BoxConS(defaultPara, H, V, x1_2Max, x1_2Min, ExpandAlongEpipoLineFlag) |
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| 40 | |
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| 41 | % [ Rc1_2 ConS1_2 RoughConS1_2] = EndPoint2BoxConS(defaultPara, H, V, x1_2Max, x1_2Min) |
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| 42 | % data structure |
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| 43 | % Rc1_2 - 4 by Num of x1_2Max = size(x1_2Max,2) |
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| 44 | |
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| 45 | Ratio2RegularMatches = 0.1; |
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| 46 | ExpandRatio = 1.25; |
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| 47 | |
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| 48 | % if ExpandAlongEpipoLineFlag == 1 |
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| 49 | % expand the search space along the epipolar line |
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| 50 | if ExpandAlongEpipoLineFlag |
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| 51 | UnitVector = x1_2Max - x1_2Min; |
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| 52 | Len = norm(UnitVector); |
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| 53 | UnitVector = UnitVector/Len; |
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| 54 | Center = (x1_2Max + x1_2Min)/2; |
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| 55 | % Calculate new x1_2Max and x1_2Min |
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| 56 | x1_2Max = Center + UnitVector*(Len/2)*ExpandRatio; |
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| 57 | x1_2Min = Center - UnitVector*(Len/2)*ExpandRatio; |
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| 58 | end |
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| 59 | |
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| 60 | % used the same concept in ../match/CalMatchSearchRegin.m |
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| 61 | |
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| 62 | tRAN = x1_2Max - x1_2Min; |
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| 63 | |
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| 64 | Ptr = tRAN(1,:) < 0; |
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| 65 | %theta_z = -atan(tRAN(2,:)./tRAN(1,:)); |
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| 66 | theta_z = atan(tRAN(2,:)./tRAN(1,:)); |
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| 67 | theta_z(Ptr) = theta_z(Ptr)+pi; |
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| 68 | Rc1_2 = [cos(-theta_z); -sin(-theta_z); sin(-theta_z); cos(-theta_z)]; |
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| 69 | ConS1_2(1:2,:) = x1_2Min; |
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| 70 | ConS1_2(3,:) = sum( Rc1_2(1:2,:).*tRAN,1);% also may check sum( Rc1_2(3:4,:).*tRAN,1) close up to zeros to verify correct or not |
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| 71 | % Re1_2 = sum( Rc1_2(3:4,:).*tRAN,1) |
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| 72 | |
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| 73 | ConS1_2(4,:) = defaultPara.VertVar*max(H,V)*Ratio2RegularMatches; |
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| 74 | % [x_origon; y_origin; x_bound, y_bound(defaultPara.VertVar*max(H,V))] |
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| 75 | |
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| 76 | % generate plot point |
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| 77 | tempConS1_2 = [ ConS1_2(3,:); ConS1_2(4,:); ... |
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| 78 | zeros(1,size(ConS1_2,2)); ConS1_2(4,:);... |
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| 79 | zeros(1,size(ConS1_2,2)); -ConS1_2(4,:);... |
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| 80 | ConS1_2(3,:); -ConS1_2(4,:)]; |
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| 81 | %Rc1_2_transpose = [cos(theta_z); sin(theta_z); -sin(theta_z); cos(theta_z)]; |
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| 82 | Rc1_2_transpose = [cos(theta_z); -sin(theta_z); sin(theta_z); cos(theta_z)]; |
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| 83 | tempConS1_2(1:2,:) = [sum( Rc1_2_transpose(1:2,:).*tempConS1_2(1:2,:), 1); ... |
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| 84 | sum( Rc1_2_transpose(3:4,:).*tempConS1_2(1:2,:), 1)]; |
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| 85 | tempConS1_2(3:4,:) = [sum( Rc1_2_transpose(1:2,:).*tempConS1_2(3:4,:), 1); ... |
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| 86 | sum( Rc1_2_transpose(3:4,:).*tempConS1_2(3:4,:), 1)]; |
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| 87 | tempConS1_2(5:6,:) = [sum( Rc1_2_transpose(1:2,:).*tempConS1_2(5:6,:), 1); ... |
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| 88 | sum( Rc1_2_transpose(3:4,:).*tempConS1_2(5:6,:), 1)]; |
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| 89 | tempConS1_2(7:8,:) = [sum( Rc1_2_transpose(1:2,:).*tempConS1_2(7:8,:), 1); ... |
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| 90 | sum( Rc1_2_transpose(3:4,:).*tempConS1_2(7:8,:), 1)]; |
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| 91 | tempConS1_2 = tempConS1_2 + repmat( x1_2Min, 4, 1); |
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| 92 | RoughConS1_2 = [ min( tempConS1_2([ 1 3 5 7],:), [], 1); max( tempConS1_2([ 1 3 5 7],:), [], 1);... |
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| 93 | min( tempConS1_2([ 2 4 6 8],:), [], 1); max( tempConS1_2([ 2 4 6 8],:), [], 1)]; |
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| 94 | |
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| 95 | % check if tRAN is zero |
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| 96 | MaskZeros = tRAN(1,:) == 0; |
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| 97 | Rc1_2(:, MaskZeros) = 0; |
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| 98 | ConS1_2(:,MaskZeros) = 0; |
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| 99 | RoughConS1_2(:,MaskZeros) = -1; |
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| 100 | return; |
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