[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 [ lamda1 lamda2 Error] = triangulation( defaultPara, R, T, x_calib) |
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| 40 | |
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| 41 | % This function generate the depth from R T and x_calib |
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| 42 | if defaultPara.TriLeastSquare |
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| 43 | Q1 = R*x_calib(1:3,:); |
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| 44 | Q2 = x_calib(4:6,:); |
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| 45 | NumRay = size(x_calib,2); |
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| 46 | b = -repmat(T, NumRay, 1); |
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| 47 | A1 = sparse(0,0); |
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| 48 | A2 = sparse(0,0); |
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| 49 | for i=1:NumRay |
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| 50 | A1 = blkdiag(A1, Q1(:,i)); |
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| 51 | A2 = blkdiag(A2, Q2(:,i)); |
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| 52 | end |
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| 53 | lamda = [A1 -A2]\b; |
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| 54 | lamda( lamda <0) = 0; |
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| 55 | lamda1 = lamda(1:NumRay)'; |
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| 56 | lamda2 = lamda((NumRay+1):end)'; |
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| 57 | Error = sqrt( sum((R*( x_calib(1:3,:).*repmat(lamda1, 3, 1)) + repmat(T, 1, size(x_calib,2)) - ... |
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| 58 | ( x_calib(4:6,:).*repmat(lamda2, 3, 1)) ).^2, 1) ); |
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| 59 | else |
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| 60 | lamda1 = sdpvar(1,size(x_calib,2)); |
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| 61 | lamda2 = sdpvar(1,size(x_calib,2)); |
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| 62 | Constrain = set(lamda1 >= 0)+set(lamda2 >= 0); |
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| 63 | sol = solvesdp(Constrain, norm( reshape( R*( x_calib(1:3,:).*repmat(lamda1, 3, 1)) + repmat(T, 1, size(x_calib,2)) - ... |
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| 64 | ( x_calib(4:6,:).*repmat(lamda2, 3, 1)), 1, []), 2), defaultPara.opt); |
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| 65 | lamda1 = double(lamda1); |
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| 66 | lamda2 = double(lamda2); |
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| 67 | |
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| 68 | Error = sqrt( sum((R*( x_calib(1:3,:).*repmat(lamda1, 3, 1)) + repmat(T, 1, size(x_calib,2)) - ... |
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| 69 | ( x_calib(4:6,:).*repmat(lamda2, 3, 1)) ).^2, 1) ); |
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| 70 | end |
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| 71 | return; |
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