% * This code was used in the following articles: % * [1] Learning 3-D Scene Structure from a Single Still Image, % * Ashutosh Saxena, Min Sun, Andrew Y. Ng, % * In ICCV workshop on 3D Representation for Recognition (3dRR-07), 2007. % * (best paper) % * [2] 3-D Reconstruction from Sparse Views using Monocular Vision, % * Ashutosh Saxena, Min Sun, Andrew Y. Ng, % * In ICCV workshop on Virtual Representations and Modeling % * of Large-scale environments (VRML), 2007. % * [3] 3-D Depth Reconstruction from a Single Still Image, % * Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng. % * International Journal of Computer Vision (IJCV), Aug 2007. % * [6] Learning Depth from Single Monocular Images, % * Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng. % * In Neural Information Processing Systems (NIPS) 18, 2005. % * % * These articles are available at: % * http://make3d.stanford.edu/publications % * % * We request that you cite the papers [1], [3] and [6] in any of % * your reports that uses this code. % * Further, if you use the code in image3dstiching/ (multiple image version), % * then please cite [2]. % * % * If you use the code in third_party/, then PLEASE CITE and follow the % * LICENSE OF THE CORRESPONDING THIRD PARTY CODE. % * % * Finally, this code is for non-commercial use only. For further % * information and to obtain a copy of the license, see % * % * http://make3d.stanford.edu/publications/code % * % * Also, the software distributed under the License is distributed on an % * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either % * express or implied. See the License for the specific language governing % * permissions and limitations under the License. % * % */ function [ maskg, maskSky]=gen_predicted_GS_efficient(Default, f, FSup) % GroundThreshold, SkyThreshold) %function [maskGvec, maskSkyvec]=gen_predicted_GS_efficient(TrainSet,HistFeaType,HistFeaDate,AbsFeaType,AbsFeaDate) % This function generated the learned Ground and Sky mask (Code by Rajiv, Modified by Min 1/27) % Input -- % f : (55x305=16775)by 104 % FSup: 13 by No. of Sup % %if nargin < 4 % GroundThreshold = 0.5; % SkyThreshold = 0.5; %elseif nargin < 5 % SkyThreshold = 0.5; %end NuRow = Default.NuRow_default; batchRow = [1:Default.WeiBatchSize:NuRow NuRow+1]; %================== maskGvec=[]; maskSkyvec=[]; for WeiBatchNumber = 1:floor(NuRow/Default.WeiBatchSize) count=1; % for i = batchRow(WeiBatchNumber):min(batchRow(WeiBatchNumber)+Default.WeiBatchSize-1,NuRow) for i = batchRow(WeiBatchNumber):batchRow(WeiBatchNumber+1)-1 % constructing features for each batch of rows from batch featuresa RowskyBottom = ceil(NuRow/2); PatchSkyBottom = ceil(Default.VertYNuDepth*(1-Default.Horizon)); if i <= RowskyBottom PatchRowRatio = PatchSkyBottom/RowskyBottom; RowTop = ceil((i-1)*PatchRowRatio+1); RowBottom = ceil(i*PatchRowRatio); else PatchRowRatio = (Default.VertYNuDepth-PatchSkyBottom)/(NuRow-RowskyBottom); RowTop = ceil((i-RowskyBottom-1)*PatchRowRatio+1)+PatchSkyBottom; RowBottom = ceil((i-RowskyBottom)*PatchRowRatio)+PatchSkyBottom; end ColumnLeft = 1; ColumnRight = Default.HoriXNuDepth; FeaVector = genFeaVectorNew( Default, f, FSup,... [RowTop:RowBottom],[ColumnLeft:ColumnRight], 1, 0); %Notice LearnNear is 0; % load the GroundSkyPara for each WeiBatchNumber load([Default.ParaFolder '/GrndSkyTheta_Train400_WeiBatNu' num2str(WeiBatchNumber) '.mat']); ab=thetaG{count}'; cd=thetaS{count}'; maskGvec=[maskGvec; ab*[ones(1,305); FeaVector]]; maskSkyvec=[maskSkyvec; cd*[ones(1,305); FeaVector]]; count=count+1; end end maskgD=maskGvec; maskSkyD=maskSkyvec; maskg=(1./(1+exp(-maskGvec)))>Default.GroundThreshold; maskSky=(1./(1+exp(-maskSkyvec)))>Default.SkyThreshold; return;