build_and_eval_model

 ==============================================================
 BUILD_AND_EVAL_MODEL: Builds a model for the set of images and points and
                       measures it.

 Code written by Katherine Smith, 2003

    GENERAL

      score = build_and_eval_model
          (image_set, points_set, norm_type)

    INPUT/S

      -image_set:
          The set of images.

      -points_set:
          The set of points.

      -norm_type:
          Normalisation type?
           
    OUTPUT/S

      -score:
           Then score of the model.

    PENDING WORK
      
      -Find out the meaning od normalisation type. 

    KNOWN BUG/S

      

    COMMENT/S

      -This does the same thingas BUILD_MODEL but also evaluates it

    RELATED FUNCTION/S

      BUILD_MODEL

    ABOUT

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

0001 function score = build_and_eval_model(image_set, points_set, norm_type)
0002 % ==============================================================
0003 % BUILD_AND_EVAL_MODEL: Builds a model for the set of images and points and
0004 %                       measures it.
0005 %
0006 % Code written by Katherine Smith, 2003
0007 %
0008 %    GENERAL
0009 %
0010 %      score = build_and_eval_model
0011 %          (image_set, points_set, norm_type)
0012 %
0013 %    INPUT/S
0014 %
0015 %      -image_set:
0016 %          The set of images.
0017 %
0018 %      -points_set:
0019 %          The set of points.
0020 %
0021 %      -norm_type:
0022 %          Normalisation type?
0023 %
0024 %    OUTPUT/S
0025 %
0026 %      -score:
0027 %           Then score of the model.
0028 %
0029 %    PENDING WORK
0030 %
0031 %      -Find out the meaning od normalisation type.
0032 %
0033 %    KNOWN BUG/S
0034 %
0035 %
0036 %
0037 %    COMMENT/S
0038 %
0039 %      -This does the same thingas BUILD_MODEL but also evaluates it
0040 %
0041 %    RELATED FUNCTION/S
0042 %
0043 %      BUILD_MODEL
0044 %
0045 %    ABOUT
0046 %
0047 %      -Created:     November 23rd, 2003
0048 %      -Last update: December 1st, 2003
0049 %      -Revision:    0.0.2
0050 %      -Author:      R. S. Schestowitz, University of Manchester
0051 % ==============================================================
0052 
0053 keep = 0.9999;
0054 [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);
0055 [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);
0056 
0057 if(norm_type == 'variance')
0058     intensity_model.sd = std(intensity_model.params);
0059     shape_model.sd = std(shape_model.params);
0060     
0061     % combine params - initially normalise to variance described in model
0062     total_shape_variance = sum(shape_model.variances);
0063     total_intensity_variance = sum(intensity_model.variances);
0064     c_model.shape_weight = ones(1,size(shape_model.pcs,2));
0065     if(total_shape_variance ~= 0)
0066         c_model.shape_weight(:) = sqrt(total_intensity_variance/total_shape_variance);
0067     % w_shapeweight(:) = sqrt(ones(1,length(w_shape_variances))*total_intensity_variance/total_shape_variance);
0068       end
0069 else
0070   error(['Unknown normalisation type: ',norm_type]);
0071 end
0072 
0073 [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);
0074 
0075 % get the combined model
0076 
0077 c_model.sd = sqrt(c_model.variances);
0078 c_model.intensity_model = intensity_model;
0079 c_model.shape_model = shape_model;
0080 c_model.n_shape_modes = size(shape_model.sd,2);
0081 c_model.label = 'Warp';
0082 
0083 score = measure_model(c_model.variances, 50);
0084  % now return the evaluation of this newly constructed model