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 [theta]= GenThetaFromPsi(x1, x2, psi); |
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40 | |
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41 | % This function is called by Matches2ViewpointTransform |
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42 | % give matches point and psi samples |
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43 | % calcuated each theta for all matches and all samples |
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44 | |
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45 | NumSample = length(psi); |
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46 | NumMatches = length(x1); |
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47 | |
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48 | % first step rotation * x1 |
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49 | R11 = permute( cos(psi), [ 1 3 2]); |
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50 | R13 = permute( sin(psi), [ 1 3 2]); |
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51 | Newx1 =[ repmat( x1(1,:), [1 1 NumSample]).*repmat( R11, [1 NumMatches 1]) + repmat( R13, [1 NumMatches 1]);... |
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52 | repmat( x1(2,:), [1 1 NumSample]);... |
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53 | repmat( x1(1,:), [1 1 NumSample]).*repmat( -R13, [1 NumMatches 1]) + repmat( R11, [1 NumMatches 1])]; %(3 x NumMatches x NumSample) |
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54 | |
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55 | % Last step find theta for each entries of Newx1 |
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56 | Interm = (Newx1(1,:,:).*repmat( x2(2,:), [1 1 NumSample]) - Newx1(2,:,:).*repmat( x2(1,:), [1 1 NumSample]))./... |
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57 | (Newx1(3,:,:).*repmat( x2(2,:), [1 1 NumSample]) + Newx1(2,:,:)); |
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58 | |
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59 | theta = atan( permute( Interm, [ 2 3 1])); |
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60 | |
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