aux_replicate_filters.m

Standard model object recognition matlab code

function f_out = aux_replicate_filters (f,num_scale_full,num_features)

% FUNCTION f_out = aux_replicate_filters (f,num_scale_full,num_features)
%
% The filter, f, may have only a few scales, so here, we merge all
% into one scale, and then replicate it to multiple scales
% (num_scale_full).  This function is used, for example, (1) to
% learn S2 features in a few scales, but replicate in all scales,
% and (2) to create 2x2 or nxn artifitial features (as in HMAX),
% but replicate in all scales.
% The arguement "num_features"  determines how many features to
% take, since there may be very many learned features.

f_tmp = merge_filters (f,num_features);
f_out = replicate_filters (f_tmp,num_scale_full);

function f_out = merge_filters (f,num_features)

% FUNCTION f_out = merge_filters (f,num_features)
%
% Here we merge all features in different scales into one scale
% (s1).  We use aux_merge_filters function.

scales = aux_get_filt_info(fieldnames(f));

% Merge all features in different scales.
f_out = [];
if length(scales) > 1
  % Put everything with 's1' (scale = 1) tag.
  f_out = aux_merge_filters (f, scales(1), f, scales(2), 's1');
  if length(scales) > 2 % merge rest of scales
    for i = 3:length(scales)
      f_out = aux_merge_filters (f_out, 1, f, scales(i), 's1');
    end
  end
else % only one scale in f
  s_tag = ['_s' num2str(scales(1))];
  f_out = setfield(f_out, 'f1_s1', getfield(f, ['f1' s_tag]));
  f_out = setfield(f_out, 'f2_s1', getfield(f, ['f2' s_tag]));
  f_out = setfield(f_out, 'i1_s1', getfield(f, ['i1' s_tag]));
  f_out = setfield(f_out, 'i2_s1', getfield(f, ['i2' s_tag]));
  f_out = setfield(f_out, 'i3_s1', getfield(f, ['i3' s_tag]));
  f_out = setfield(f_out, 'size_s1', getfield(f, ['size' s_tag]));
  f_out = setfield(f_out, 'shift_s1', getfield(f, ['shift' s_tag]));
end

% Now get the merged fields.
f_f1 = getfield(f_out, 'f1_s1');
f_f2 = getfield(f_out, 'f2_s1');
f_i1 = getfield(f_out, 'i1_s1');
f_i2 = getfield(f_out, 'i2_s1');
f_i3 = getfield(f_out, 'i3_s1');
f_size = getfield(f_out, 'size_s1');

% There can be quite a large number of features, so take the
% specified number of features.  If you want to take the random
% features, you will have to randomize the input f, in the first
% place.  Since we probably want to use the same features over and
% over again, we do NOT extract random features here.

if num_features <= f_size(4)
  which_features = [1:num_features];
  f_size(4) = num_features;
else 
  % There are not that many features, so pick all features.
  which_features = [1:f_size(4)];
  disp('Requested too many features.');
end

f_out = setfield(f_out, 'f1_s1', f_f1(:,which_features));
f_out = setfield(f_out, 'f2_s1', f_f2(:,which_features));
f_out = setfield(f_out, 'i1_s1', f_i1(:,which_features));
f_out = setfield(f_out, 'i2_s1', f_i2(:,which_features));
f_out = setfield(f_out, 'i3_s1', f_i3(:,which_features));
f_out = setfield(f_out, 'size_s1', f_size);

function f_out = replicate_filters (f, num_scale_full)

% FUNCTION f_out = replicate_filters (f, num_scale_full)
%
% Replicate filter f in all scale (1 through num_scale_full).  
% In the previous function (merge_filters), all filters are put
% into "s1" scale.

%f_f1 = getfield(f, 'f1_s1');
%f_f2 = getfield(f, 'f2_s1');
%f_i1 = getfield(f, 'i1_s1');
%f_i2 = getfield(f, 'i2_s1');
%f_i3 = getfield(f, 'i3_s1');

% It is a waste of memory to copy and store all the same filters.
% Therefore, a blank field is stored in the first scale 's1', and in
% comp_get_next_layer, we see if the filters in the higher scale are [].
f_f1 = [];
f_f2 = [];
f_i1 = [];
f_i2 = [];
f_i3 = [];
f_size = getfield(f, 'size_s1');
f_shift = getfield(f, 'shift_s1');

f_out = f;
for i = 2:num_scale_full 
  scale_tag = ['s' num2str(i)];
  f_out = setfield(f_out, ['f1_' scale_tag], f_f1);
  f_out = setfield(f_out, ['f2_' scale_tag], f_f2);
  f_out = setfield(f_out, ['i1_' scale_tag], f_i1);
  f_out = setfield(f_out, ['i2_' scale_tag], f_i2);
  f_out = setfield(f_out, ['i3_' scale_tag], f_i3);
  f_out = setfield(f_out, ['size_' scale_tag], f_size);
  f_out = setfield(f_out, ['shift_' scale_tag], f_shift);
end