global-local-affinity-graph

source code for the paper "A global/local affinity graph for image segmentation"

here is the code to generate the table IV for our paper

• you could also extract only part of this code easily to port single

  different graph tp generate the table I

• to get our global/local affinity graph, you could just keep the local graph and LO graph, for example:

W_L0 = compute_region_similarity_Sparse_penalty(feature,3,centroid,Area);
W_GLG=assignGraphValue(W,W_L0,global_nodes);

• to combine different feature descriptor,
  • first just change the following feature=feat{k}.mlab; - here is the list you could change:

 {'mlab';

    'ch';

     'lbp';

     'siftbow100';

     'siftbow150';

     'siftbow200';

     'siftbow300'};

• then you compute the affinity graph W_GLG_mlab,W_GLG_lbp, etc.,

• finally, you combine them according to the fusion equation in our paper Eq.11-12

Please Note that you may not generate the exact performance listed in our paper,