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 [Position3D ImgPositionWrl] = PreWrlData(K, Depth, I, R, T) |
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40 | |
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41 | % This function prepare the data for WrlFacestHoriReduce to use |
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42 | [VDepth HDepth] = size(Depth); |
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43 | [VImg HImg] = size(I); |
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44 | VIndexDepthRes = repmat((1:VDepth)', [1 HDepth]); |
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45 | HIndexDepthRes = repmat((1:HDepth), [VDepth 1]); |
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46 | VIndexImgRes = ( VIndexDepthRes -0.5)/VDepth*VImg; |
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47 | HIndexImgRes = ( HIndexDepthRes -0.5)/HDepth*HImg; |
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48 | ImgPositionPix = cat(3, HIndexImgRes, VIndexImgRes); |
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49 | Position3D = inv(K)*reshape( permute(cat(3, ImgPositionPix, ones(VDepth, HDepth)), [3 1 2]), 3, []); |
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50 | Position3D = Position3D./repmat( sqrt(sum(Position3D.^2, 1)), 3, 1); |
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51 | Position3D = Position3D.*repmat( Depth(:)', 3, 1); |
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52 | |
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53 | % rotation and translation |
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54 | Position3D = R*Position3D+repmat(T, 1, size(Position3D,2)); |
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55 | |
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56 | Position3D = reshape( Position3D, 3, VDepth, []); |
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57 | Position3D = permute( Position3D, [ 2 3 1]); |
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58 | Position3D(:,:,3) = -Position3D(:,:,3); |
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59 | |
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60 | VIndexWrl = (VImg+1-VIndexImgRes - 0.5)/VImg; |
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61 | HIndexWrl = (HIndexImgRes - 0.5)/HImg; |
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62 | ImgPositionWrl = cat(3, HIndexWrl, VIndexWrl); |
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63 | return; |
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64 | |
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