[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 []=CalFeaturesOld(FeaBatchNumber,HistFeaType,AbsFeaType); |
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| 40 | %function []=CalFeatures(taskName,ImgFolder,TrainSet,LearnType,LearnSkyEx,LearnLog,LearnNear,... |
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| 41 | % LearnAlg,LearnDate,AbsFeaType,AbsFeaDate,HistFeaType,HistFeaDate, ... |
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| 42 | % GeneralDataFolder, ScratchDataFolder, LocalFolder, ClusterExecutionDirectory, FeaBatchNumber) |
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| 43 | % This funciton is the meta funciton to choose different feature calculation method |
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| 44 | global GeneralDataFolder ScratchDataFolder LocalFolder ClusterExecutionDirectory... |
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| 45 | ImgFolder VertYNuPatch VertYNuDepth HoriXNuPatch HoriXNuDepth a_default b_default Ox_default Oy_default... |
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| 46 | Horizon_default filename batchSize NuRow_default SegVertYSize SegHoriXSize WeiBatchSize PopUpVertY PopUpHoriX taskName... |
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| 47 | TrainVerYSize TrainHoriXSize MempryFactor; |
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| 48 | |
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| 49 | |
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| 50 | |
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| 51 | |
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| 52 | %HistFeaType |
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| 53 | %AbsFeaType |
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| 54 | %switch AbsFeaType |
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| 55 | % case 'Whole' |
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| 56 | gen_feature_filt1D_sepH2H4_fixMem(FeaBatchNumber,HistFeaType,1); |
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| 57 | % disp('AbsFeaType is Whole'); |
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| 58 | %gen_feature_general(taskName,ImgFolder,TrainSet,LearnType,LearnSkyEx,LearnLog,LearnNear,... |
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| 59 | % LearnAlg,LearnDate,AbsFeaType,AbsFeaDate,HistFeaType,HistFeaDate, ... |
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| 60 | % GeneralDataFolder, ScratchDataFolder, LocalFolder, ClusterExecutionDirectory, FeaBatchNumber,1); |
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| 61 | %case 'Sub' |
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| 62 | % disp('AbsFeaType is Subsuperpixel'); |
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| 63 | % gen_feature_sep(FeaBatchNumber,HistFeaType,1); |
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| 64 | % case 'WholeH13' %Calculate Histogram based features |
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| 65 | % disp('AbsFeaType is WholeH13'); |
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| 66 | % gen_feature_H1_H3(FeaBatchNumber,HistFeaType,1); |
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| 67 | %otherwise |
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| 68 | % disp('AbsFeaType is None.'); |
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| 69 | % gen_feature_sep(FeaBatchNumber,HistFeaType,0); |
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| 70 | %end |
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| 71 | return; |
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