build_model

 ==============================================================
 BUILD_MODEL: Builds a model for the set of images and points.

 Code written by Katherine Smith, 2003

    GENERAL

      c_model = build_model(image_set, points_set, 
                 keep, label, norm_type, shape_weight)


    INPUT/S

      -image_set:
           The input images set.

      -points_set:
           The input points set.

      -keep:
           The precision required from PCA??

      -label:
           Label of the model created?

      -norm_type:


      -shape_weight:
          The value of Ws which is the weighing factor in the model.

           
    OUTPUT/S

      -c_model:
           The model built.

    PENDING WORK

      Review input/output documentation.

    KNOWN BUG/S

      

    COMMENT/S

      -This also resembles some parts of eval_app_model_obj_fn.
      -same as BUILD_AND_EVAL but no evaluation at bottom.

    RELATED FUNCTION/S

      BUILD_AND_EVALUATE_MODEL

    ABOUT

      -Created:     November 23rd, 2003
      -Last update: December 1st, 2003
      -Revision:    0.0.2
      -Author:      R. S. Schestowitz, University of Manchester
 ==============================================================

0001 function c_model = build_model(image_set, points_set, keep, label, norm_type, shape_weight)
0002 % ==============================================================
0003 % BUILD_MODEL: Builds a model for the set of images and points.
0004 %
0005 % Code written by Katherine Smith, 2003
0006 %
0007 %    GENERAL
0008 %
0009 %      c_model = build_model(image_set, points_set,
0010 %                 keep, label, norm_type, shape_weight)
0011 %
0012 %
0013 %    INPUT/S
0014 %
0015 %      -image_set:
0016 %           The input images set.
0017 %
0018 %      -points_set:
0019 %           The input points set.
0020 %
0021 %      -keep:
0022 %           The precision required from PCA??
0023 %
0024 %      -label:
0025 %           Label of the model created?
0026 %
0027 %      -norm_type:
0028 %
0029 %
0030 %      -shape_weight:
0031 %          The value of Ws which is the weighing factor in the model.
0032 %
0033 %
0034 %    OUTPUT/S
0035 %
0036 %      -c_model:
0037 %           The model built.
0038 %
0039 %    PENDING WORK
0040 %
0041 %      Review input/output documentation.
0042 %
0043 %    KNOWN BUG/S
0044 %
0045 %
0046 %
0047 %    COMMENT/S
0048 %
0049 %      -This also resembles some parts of eval_app_model_obj_fn.
0050 %      -same as BUILD_AND_EVAL but no evaluation at bottom.
0051 %
0052 %    RELATED FUNCTION/S
0053 %
0054 %      BUILD_AND_EVALUATE_MODEL
0055 %
0056 %    ABOUT
0057 %
0058 %      -Created:     November 23rd, 2003
0059 %      -Last update: December 1st, 2003
0060 %      -Revision:    0.0.2
0061 %      -Author:      R. S. Schestowitz, University of Manchester
0062 % ==============================================================
0063 
0064 [intensity_model.pcs,intensity_model.variances,intensity_model.params, intensity_model.mean, intensity_model.var_r, intensity_model.total_var, intensity_model.impdata] = st_pca(image_set', keep);
0065 [shape_model.pcs,shape_model.variances,shape_model.params, shape_model.mean, shape_model.var_r, shape_model.total_var, shape_model.impdata] = st_pca(points_set', keep);
0066    % get shape and intensity model
0067 c_model.shape_weight = ones(1,size(shape_model.pcs,2));
0068    % set weight to be a column vector of 1's? Would that mean equal weighing for shape and intensity?
0069 intensity_model.sd = std(intensity_model.params);
0070   % get and record standard deviation
0071 shape_model.sd = std(shape_model.params);
0072 if (strcmp(norm_type,'variance')),    
0073     % combine params - initially normalise to variance described in model
0074     total_shape_variance = sum(shape_model.variances);
0075     total_intensity_variance = sum(intensity_model.variances);
0076     if(total_shape_variance ~= 0)
0077         c_model.shape_weight(:) = sqrt(total_intensity_variance/total_shape_variance);
0078     end
0079 %     disp(['Shapeweight: ',num2str(c_model.shape_weight(1))]);
0080 elseif (strcmp(norm_type,'constant')),
0081       c_model.shape_weight(:) = shape_weight;
0082          % simply assign the predefined value
0083 elseif (strcmp(norm_type,'edge')),
0084       edges = abs(diff(image_set,1,2));
0085       mean_edge_strength = sum(edges(:))/size(edges(:),1);
0086       c_model.shape_weight(:) = mean_edge_strength;
0087 %     disp(['edge weight: ',num2str(mean_edge_strength)]);
0088 else
0089       error(['Unknown normalisation type: ',norm_type]);
0090 end
0091 
0092 [c_model.pcs, c_model.variances, c_model.params, c_model.mean, c_model.total_var, c_model.impdata] = make_combined_model(shape_model, intensity_model, c_model.shape_weight);
0093 c_model.sd = sqrt(c_model.variances);
0094 c_model.intensity_model = intensity_model;
0095 
0096 % intensity_model
0097 % shape_model
0098 % figure;
0099 % plot(intensity_model);
0100         % attempt to look at the models built from the data (RSS)
0101 
0102 c_model.shape_model = shape_model;
0103 c_model.n_shape_modes = size(shape_model.sd,2);
0104 c_model.label = label;
0105    % save some of the values to be returned by the function