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 | % This function setup all the nessesary initialization for all the process in |
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40 | % image3dstiching folder or sub-folder |
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41 | |
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42 | % Set Path |
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43 | addpath(genpath('./')); |
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44 | |
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45 | % Old function (should not be used anymore) |
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46 | %addpath(genpath('../multipleImages')); % Old function |
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47 | |
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48 | % general function |
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49 | addpath(genpath('../third_party/lightspeed')); % lightspeed |
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50 | addpath(genpath('../third_party/torr/')); % torr/ |
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51 | addpath(genpath('../third_party/vlutil')); % vlutil |
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52 | addpath(genpath('../third_party/zisserman')); % zisserman |
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53 | addpath(genpath('../third_party/local_ext_mod')); % function to find Local min, max, nearest neighbour |
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54 | addpath(genpath('../third_party/fmatrix')); % function to do F estimation |
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55 | |
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56 | % Quaternion toolbox |
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57 | addpath(genpath('../third_party/qtfm')); |
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58 | |
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59 | % Projective Reconstruction function |
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60 | addpath(genpath('../third_party/missing-dat')); %missing-data |
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61 | |
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62 | % feature matching function |
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63 | addpath(genpath('../third_party/SURF-V1.0.8')); % SURF |
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64 | addpath(genpath('../third_party/sift')); % SIFT |
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65 | addpath(genpath('../third_party/kovesi')); % Ransac |
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66 | |
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67 | % sfm function |
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68 | addpath(genpath('../third_party/sba-1.3')); % Non-linear solver (sparse Levenberg-Marquardt algorithm) |
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69 | |
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70 | % opt function |
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71 | addpath(genpath('../third_party/opt')); % OPT solver |
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72 | |
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73 | % LearningCode functions |
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74 | addpath(genpath('../LearningCode')); % learned depth and plane parameter functions |
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75 | % other need for LearningCode |
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76 | addpath(genpath('../third_party/EdgeLinkLineSegFit/')); % EdgeLinkLineSegFit/ |
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77 | |
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78 | % image rectification |
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79 | addpath(genpath('../third_party/RectifKitE')); |
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80 | |
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81 | % Fast 2D normalized cross-corrleation |
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82 | addpath(genpath('../third_party/normxc_cpp/')); % normxc_cpp/ |
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