source: proiecte/pmake3d/make3d_original/Make3dSingleImageStanford_version0.1/LearningCode/Features/OldBatchVersion/GenTextureFeature.m @ 86

% *  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 [TextureFeature]=GenTextureFeature(Default, Img, SmallSup, HiSup, FeatureType)

% This function calculate all features that using the
% output from calculateFilterBanks_old (Time and ram comsuming)
% These Feature including AbsFeature DiffFeature HistogramFeature
% FeatureTypr:            1          2           3 

% Interface:
% Input---
% 1) Default is the structure contain all the default parameter setting
% 2) Img is the RGB image matrix
% 3) SmallSup is Superpixel index matrix of size Default.VertYNuDepth Default.HoriXNuDepth
% 4) HiSup is HiResolution Superpixel index matrix of size Default.SegVertYSize Default.SegHoriXSize or smaller
% 5) FeatureType AbsFeature(1) DiffFeature(2) HistogramFeature(3)
% Output---
% 1) TextureFeature.Abs:
% 2) TextureFeature.Diff:
% 3) TextureFeature.Hist:


% Flag set up for testing purpose ========================================
% Must be stablized after testing XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
NormalizeFlag = 1; % NormalizeFlag set to 1 if we want to normalize the Feature according to the Trainning Set
DominateSupFilter = 1; % DominateSupFilter set to 1 if we want to use only the dominate superpixel area for acerage feature calculation
% ========================================================================

% load FeaMax to do normalizeing
load([Default.GeneralDataFolder '/FeaMax.mat']);
if NormalizeFlag == 1
   FeaMax = 10.^floor(log10(FeaMax));
else
   FeaMax(:) = 1;
end

% Initial Setting of TextureFeature Structure:
% size(TextureFeature.Abs) = (No of Depth Point, No of Features: 17 texture filters, H2 and H4 kinds, 3 Scales)
TextureFeature.Abs = zeros(Default.VertYNuDepth*Default.HoriXNuDepth, 17*2*3);
TextureFeature.Diff = zeros(1,1);
TextureFeature.Hist = zeros(1,1);

% Start the loop for 3 Scale
fInd = 2;
for i = 1:3
    
    if DominateSupFilter && i==1 % only if DominateSupFilter and the largest scale will use superpixel mask
       SupMaskFlag = 1;
    else 
       SupMaskFlag = 0;
    end  
 
    % Scale Setting
    ResY = round(Default.TrainVerYSize/(3^(i-1))); % ResY ResX will be the new image size     
    ResX = round(Default.TrainHoriXSize/(3^(i-1)));
    Img = imresize(Img,[ResY ResX],'nearest');

    % Generate the 17 texture filter output
    [H2] = calculateFilterBanks_old(Img); % (hard work 1min) use Ashutaosh's code
    H2 = H2.^2; % Now H2 stand for H2 22222222222222222222222222222222222222222222222222222222222222222222222222222
 
    if any(FeatureType == 1) % calculate the AbsFeatures
       StartAbs = 34*(i-1)+1;
%       [TextureFeature.Abs(:, (StartAbs):(StartAbs+16)) fInd]= AbsFeatureGenMex(Default, H2, SmallSup, HiSup, SupMaskFlag, FeaMax, fInd);
       [TextureFeature.Abs(:, (StartAbs):(StartAbs+16)) fInd]= AbsFeatureGenMex(Default, H2, SmallSup, HiSup, SupMaskFlag, FeaMax, fInd);
    end

    if any(FeatureType == 3) % calculate the HistogramFeature
       [relativeFeatureVector] = makeRelativeFeatureVector(H2,1);
    end

    if any(FeatureType == 2) % calculate the DiffFeature

    end
    % 2222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222

    H2 = H2.^2; % This H2 is H4 44444444444444444444444444444444444444444444444444444444444444444444444444444444444

    if any(FeatureType == 1) % calculate the AbsFeatures
       StartAbs = 34*(i-1)+1+17;
%       [TextureFeature.Abs(:, (StartAbs):(StartAbs+16)) fInd]= AbsFeatureGenMex(Default, H2, SmallSup, HiSup, SupMaskFlag, FeaMax, fInd);
       [TextureFeature.Abs(:, (StartAbs):(StartAbs+16)) fInd]= AbsFeatureGenMex(Default, H2, SmallSup, HiSup, SupMaskFlag, FeaMax, fInd);
    end
    % 44444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444
    clear H2;
end

return;