LearnS2Template

 LearnS2Template - Learns an active basis template for Ellipsoid, angle,
   and parallel bars.

0001 % LearnS2Template - Learns an active basis template for Ellipsoid, angle,
0002 %   and parallel bars.
0003 
0004 clear all; close all; 
0005 disp('===============> Learning the active basis model from positive training images');
0006 
0007 load ../template_params
0008 
0009 %% Template 1: Ellipsoid
0010 % generate the training image for the first template: ellisoid
0011 numImage = 1; % number of training images
0012 I = cell(numImage, 1);
0013 sizex = 63; sizey = 63;
0014 center = 32; a = 22; b = 10;
0015 I0 = single(zeros(sizex, sizey)); 
0016 for x = 1:sizex
0017         for y = 1:sizey
0018             if (((x-center)/a)^2+((y-center)/b)^2<1.)
0019                 I0(x, y) = single(1.); 
0020             end
0021         end
0022 end
0023 I{1} = I0+0.;
0024 
0025 allSizex = zeros(1, numImage, 'single')+sizex; 
0026 allSizey = zeros(1, numImage, 'single')+sizey;
0027 
0028 % use the 4th scale
0029 s = 4;
0030 storeName = ['../result/naturalStat' num2str(s-1)];
0031 load(storeName);
0032 numElement = 14;
0033 halfFilterSize = ( size(GaborFilter{(s-1)*nGaborOri+1},1) - 1 ) / 2;
0034 disp(['start filtering training images at Gabor length ' num2str(2*halfFilterSize+1)]); tic
0035 
0036 selectedOrient = zeros(numElement, 1, 'single');  % orientation and location of selected Gabors
0037 selectedx = zeros(numElement, 1, 'single');
0038 selectedy = zeros(numElement, 1, 'single');
0039 selectedlambda = zeros(numElement, 1, 'single'); % weighting parameter for scoring template matching
0040 selectedLogZ = zeros(numElement, 1, 'single'); % normalizing constant
0041 symbolicTemplate = zeros(sizex, sizey, 'single'); % template of active basis
0042 
0043 
0044 % Compute SUM1 maps by Gabor filtering
0045 SUM1map = applyfilterMultiScale(I, GaborFilter((s-1)*nGaborOri+(1:nGaborOri)), nGaborOri); % SUM1 maps by Gabor filtering
0046 disp(['filtering time: ' num2str(toc) ' seconds']);
0047 
0048 % Compute MAX1 maps and record the track maps
0049 locationShiftLimit = 0; % shift in normal direction = locationShiftLimit*subsample pixels
0050 orientShiftLimit = 0; % shift in orientation
0051 Csigmoid(numImage, allSizex, allSizey, nGaborOri, GaborSaturation, SUM1map);
0052 MAX1map = cell(numImage, nGaborOri);
0053 subsampleM1 = 1;  % to be safe, please refrain from setting it to be larger than 1
0054 trackMap = cell(numImage, nGaborOri);
0055 for img = 1:numImage
0056     for orient = 1:nGaborOri
0057         MAX1map{img, orient} = single(zeros(floor(sizex/subsampleM1), floor(sizey/subsampleM1))); 
0058         trackMap{img, orient} = single(zeros(floor(sizex/subsampleM1), floor(sizey/subsampleM1))); 
0059     end
0060 end
0061 disp(['start maxing training images at Gabor length ' num2str(2*halfFilterSize+1)]); tic
0062 CgetMAX1track(numImage, allSizex, allSizey, nGaborOri, locationShiftLimit, orientShiftLimit, subsampleM1, ...
0063               SUM1map, MAX1map, trackMap);
0064 disp(['maxing time: ' num2str(toc) ' seconds']);
0065 
0066 
0067 % Learning by shared sketch algorithm
0068 learningSampleSize = 1;
0069 deformedTemplate = cell(1, learningSampleSize); % templates for training images
0070 for img = 1 : learningSampleSize
0071     deformedTemplate{img} = single(zeros(sizex, sizey));  
0072 end
0073 SUM2score = zeros(learningSampleSize, 1); % template matching scores for training images
0074 disp(['start mex-C learning of template at Gabor length ' num2str(2*halfFilterSize+1)]); tic
0075 CsharedSketch(nGaborOri, locationShiftLimit, orientShiftLimit, GaborSaturation, subsampleM1, ... % about active basis  
0076        numElement, learningSampleSize, sizex, sizey, ...
0077        SUM1map, MAX1map, trackMap, ... % about training images 
0078        halfFilterSize, CorrGabor((s-1)*nGaborOri + (1:nGaborOri), (s-1)*nGaborOri + (1:nGaborOri)),...
0079        GaborSymbol( (s-1)*nGaborOri + (1:nGaborOri) ), ... % about filters
0080        numStoredPoint, (storedLambda), (storedExpectation), (storedLogZ), ... % about exponential model 
0081        selectedOrient, selectedx, selectedy, selectedlambda, selectedLogZ, SUM2score, ... % learned parameters
0082        symbolicTemplate, deformedTemplate); % learned templates
0083 
0084 selectedScale = ones(numElement,1)*(s-1); % the scale index starts from 0
0085 S2Template{1} = struct('numElement',numElement,'selectedOrient',selectedOrient,...
0086     'selectedx',selectedx,'selectedy',selectedy,'selectedScale',selectedScale,...
0087     'selectedlambda',selectedlambda,'selectedLogZ',selectedLogZ,...
0088     'sizex',sizex,'sizey',sizey,'symbolicTemplate',symbolicTemplate,...
0089     'subsampleM1',subsampleM1);
0090 
0091 
0092 %% Learn the second S2 template: angle
0093 im = imread('angle1.png');
0094 if size(im,3) == 3
0095     im = rgb2gray(im);
0096 end
0097 im = single(imresize(im,0.15));
0098 im(im < 250) = 0;
0099 im(im >= 250) = 1;
0100 I{1} = im;
0101 [sizex sizey] = size(im);
0102 allSizex = single(sizex); allSizey = single(sizey);
0103 numElement = 14;
0104 halfFilterSize = ( size(GaborFilter{(s-1)*nGaborOri+1},1) - 1 ) / 2;
0105 disp(['start filtering training images at Gabor length ' num2str(2*halfFilterSize+1)]); tic
0106 
0107 selectedOrient = zeros(numElement, 1, 'single');  % orientation and location of selected Gabors
0108 selectedx = zeros(numElement, 1, 'single');
0109 selectedy = zeros(numElement, 1, 'single');
0110 selectedlambda = zeros(numElement, 1, 'single'); % weighting parameter for scoring template matching
0111 selectedLogZ = zeros(numElement, 1, 'single'); % normalizing constant
0112 symbolicTemplate = zeros(sizex, sizey, 'single'); % template of active basis
0113 
0114 % Compute SUM1 maps by Gabor filtering
0115 SUM1map = applyfilterMultiScale(I, GaborFilter((s-1)*nGaborOri+(1:nGaborOri)), nGaborOri); % SUM1 maps by Gabor filtering
0116 disp(['filtering time: ' num2str(toc) ' seconds']);
0117 
0118 % Compute MAX1 maps and record the track maps
0119 locationShiftLimit = 0; % shift in normal direction = locationShiftLimit*subsample pixels
0120 orientShiftLimit = 0; % shift in orientation
0121 Csigmoid(numImage, allSizex, allSizey, nGaborOri, GaborSaturation, SUM1map);
0122 MAX1map = cell(numImage, nGaborOri);
0123 subsampleM1 = 1;  % to be safe, please refrain from setting it to be larger than 1
0124 trackMap = cell(numImage, nGaborOri);
0125 for img = 1:numImage
0126     for orient = 1:nGaborOri
0127         MAX1map{img, orient} = single(zeros(floor(sizex/subsampleM1), floor(sizey/subsampleM1))); 
0128         trackMap{img, orient} = single(zeros(floor(sizex/subsampleM1), floor(sizey/subsampleM1))); 
0129     end
0130 end
0131 disp(['start maxing training images at Gabor length ' num2str(2*halfFilterSize+1)]); tic
0132 CgetMAX1track(numImage, allSizex, allSizey, nGaborOri, locationShiftLimit, orientShiftLimit, subsampleM1, ...
0133               SUM1map, MAX1map, trackMap);
0134 disp(['maxing time: ' num2str(toc) ' seconds']);
0135 
0136 
0137 % Learning by shared sketch algorithm
0138 learningSampleSize = 1;
0139 deformedTemplate = cell(1, learningSampleSize); % templates for training images
0140 for img = 1 : learningSampleSize
0141     deformedTemplate{img} = single(zeros(sizex, sizey));  
0142 end
0143 SUM2score = zeros(learningSampleSize, 1); % template matching scores for training images
0144 disp(['start mex-C learning of template at Gabor length ' num2str(2*halfFilterSize+1)]); tic
0145 CsharedSketch(nGaborOri, locationShiftLimit, orientShiftLimit, GaborSaturation, subsampleM1, ... % about active basis  
0146        numElement, learningSampleSize, sizex, sizey, ...
0147        SUM1map, MAX1map, trackMap, ... % about training images 
0148        halfFilterSize, CorrGabor((s-1)*nGaborOri + (1:nGaborOri), (s-1)*nGaborOri + (1:nGaborOri)),...
0149        GaborSymbol( (s-1)*nGaborOri + (1:nGaborOri) ), ... % about filters
0150        numStoredPoint, (storedLambda), (storedExpectation), (storedLogZ), ... % about exponential model 
0151        selectedOrient, selectedx, selectedy, selectedlambda, selectedLogZ, SUM2score, ... % learned parameters
0152        symbolicTemplate, deformedTemplate); % learned templates
0153 
0154 selectedScale = ones(numElement,1)*(s-1); % the scale index starts from 0
0155 
0156 S2Template{2} = struct('numElement',numElement,'selectedOrient',selectedOrient,...
0157     'selectedx',selectedx,'selectedy',selectedy,'selectedScale',selectedScale,...
0158     'selectedlambda',selectedlambda,'selectedLogZ',selectedLogZ,...
0159     'sizex',sizex,'sizey',sizey,'symbolicTemplate',symbolicTemplate,...
0160     'subsampleM1',subsampleM1);
0161 
0162 %% The third template: a long bar
0163 selectedx = single([0 0 0 0 0 0 15 15 15 15 15 15]);
0164 selectedy = single([0 10 20 30 40 50 0 10 20 30 40 50]-30);
0165 selectedOrient = single([0 0 0 0 0 0 0 0 0 0 0 0]);
0166 % modified the scale!!!
0167 selectedScale = ones(numElement,1)*(s-1+1); % the scale index starts from 0
0168 numElement = length(selectedx);
0169 selectedlambda = 0.6*ones(numElement, 1, 'single'); % weighting parameter for scoring template matching
0170 selectedLogZ = 1.2*ones(numElement, 1, 'single'); % normalizing constant
0171 sym = displayTemplate( ...
0172             selectedx,selectedy,selectedOrient, selectedScale, ones(numElement,1),...
0173             GaborSymbol,nGaborOri,subsampleM1);
0174 S2Template{3} = struct('numElement',numElement,'selectedOrient',selectedOrient,...
0175     'selectedx',selectedx,'selectedy',selectedy,'selectedScale',selectedScale,...
0176     'selectedlambda',selectedlambda,'selectedLogZ',selectedLogZ,...
0177     'sizex',sizex,'sizey',sizey,'symbolicTemplate',sym,...
0178     'subsampleM1',subsampleM1);
0179 
0180 %% save results
0181 disp(['mex-C learning time: ' num2str(toc) ' seconds']);
0182 templateName = ['../result/learnedS2Template'];
0183 save(templateName, 'S2Template');
0184 
0185