[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 | |
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| 40 | image3dstichingSetPath |
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| 41 | Fdir = '/afs/cs/group/reconstruction3d/scratch/TestMultipleImage/COM4_070525_001900_gates/data' |
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| 42 | defaultPara.Fdir = '/afs/cs/group/reconstruction3d/scratch/TestMultipleImage/COM4_070525_001900_gates' |
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| 43 | load([ Fdir '/ImgInfo.mat']); |
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| 44 | [ MatchesUnified]= MergeMatchesData(Fdir,{'MatchesType', 'MatchesType2','MatchesType3'}); |
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| 45 | % ----------- modified the match - |
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| 46 | BadPairList = []; |
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| 47 | BadPairList = [BadPairList; {'IMG_0666','IMG_0674'}]; |
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| 48 | BadPairList = [BadPairList; {'IMG_0670','IMG_0683'}]; |
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| 49 | BadPairList = [BadPairList; {'IMG_0670','IMG_0684'}]; |
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| 50 | BadPairList = [BadPairList; {'IMG_0671','IMG_0674'}]; |
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| 51 | BadPairList = [BadPairList; {'IMG_0671','IMG_0683'}]; |
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| 52 | BadPairList = [BadPairList; {'IMG_0671','IMG_0684'}]; |
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| 53 | BadPairList = [BadPairList; {'IMG_0673','IMG_0674'}]; |
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| 54 | BadPairList = [BadPairList; {'IMG_0673','IMG_0683'}]; |
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| 55 | BadPairList = [BadPairList; {'IMG_0674','IMG_0679'}]; |
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| 56 | |
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| 57 | GoodPairList = []; |
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| 58 | GoodPairList = [ GoodPairList; {'IMG_0664','IMG_0668'}]; |
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| 59 | GoodPairList = [ GoodPairList; {'IMG_0668','IMG_0674'}]; |
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| 60 | GoodPairList = [ GoodPairList; {'IMG_0674','IMG_0676'}]; |
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| 61 | GoodPairList = [ GoodPairList; {'IMG_0676','IMG_0677'}]; |
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| 62 | GoodPairList = [ GoodPairList; {'IMG_0677','IMG_0678'}]; |
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| 63 | [MatchesUnified] = ModifyMatch(ImgInfo, MatchesUnified, GoodPairList, 1); |
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| 64 | % -------------------------------- |
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| 65 | [ track]=TrackBuilding(MatchesUnified); |
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| 66 | [ CleanedMatches]=Track2Match(track) |
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| 67 | |
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| 68 | NuPair = size(GoodPairList,1); |
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| 69 | for i = 1:NuPair |
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| 70 | [ImgAIndex] = ImgInfoIndexFromName(ImgInfo, GoodPairList{i,1}) |
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| 71 | [ImgBIndex] = ImgInfoIndexFromName(ImgInfo, GoodPairList{i,2}) |
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| 72 | Img1 = strrep(ImgInfo(ImgAIndex).ExifInfo.name,'.jpg',''); |
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| 73 | Img2 = strrep(ImgInfo(ImgBIndex).ExifInfo.name,'.jpg',''); |
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| 74 | matches = [CleanedMatches(ImgAIndex, ImgBIndex).Index; CleanedMatches(ImgBIndex, ImgAIndex).Index ]; |
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| 75 | matches_ori = [MatchesUnified(ImgAIndex, ImgBIndex).Index; MatchesUnified(ImgBIndex, ImgAIndex).Index ]; |
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| 76 | |
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| 77 | I1=imreadbw([defaultPara.Fdir '/pgm/' Img1 '.pgm']); % function from sift |
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| 78 | I2=imreadbw([defaultPara.Fdir '/pgm/' Img2 '.pgm']); % function from sift |
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| 79 | [f1] = readSurf(Img1, defaultPara.Fdir, 'Dense'); % original features |
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| 80 | [f2] = readSurf(Img2, defaultPara.Fdir, 'Dense'); % original features |
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| 81 | |
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| 82 | figure(11); plotmatches(I1,I2,f1, f2, matches, 'Stacking','v','Interactive', 2); |
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| 83 | saveas(11,[ Fdir '/cleanMatch/' Img1 '_' Img2 'CleanedMatch'],'jpg'); |
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| 84 | figure(12); plotmatches(I1,I2,f1, f2, matches_ori([2 1],:), 'Stacking','v','Interactive', 2); |
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| 85 | saveas(12,[ Fdir '/cleanMatch/' Img1 '_' Img2 'OriMatch'],'jpg'); |
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| 86 | end |
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| 87 | |
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