README

This is the supporting code for "Category Independent Object Proposals" by Ian Endres and Derek Hoiem, University of Illinois at Urbana-Champaign, ECCV 2010


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LICENSE:

Copyright (C) 2010 Ian Endres, University of Illinois at Urbana-Champaign

This program is free software; you can redistribute it and/or modify it
under the terms of the GNU General Public License as published by the
Free Software Foundation; either version 2 of the License, or (at your
option) any later version.

This program is distributed in the hope that it will be useful but
WITHOUT WARRANTY; without even the implied warranty of MERCHANTABILITY
or FITNESS FOR A PARTICULAR PUPROSE.  See the GNU General Public License

You should have received a copy of the GNU General Public License along with
this program; if not, write to the Free Software Foundation, Inc.,
59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
Details of GPL License available in GNU_GPL_License.txt at base of this
source tree.

This software is only available for non-commercial use.  Contact Ian
Endres (iendres2@uiuc.edu) with questions regarding commercial licensing.
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For 64-bit linux machines, this code should be ready to run, with all of the appropriate files already compiled.
Update 9/21/2010: I have also compiled it for 32-bit linux.

Both are compiled and tested using: Matlab Version 7.9.0.529 (R2009b)

64-bit Windows binaries have also been included and tested on Windows 7 with Matlab Version 7.9.0.529 (R2009b)
Note that these were compiled using Visual Studio 2008, and requires that the run-time libraries to be installed.

Simply call:
addpath(genpath('proposals'))

[proposals superpixels] = generate_proposals('proposals/car.jpg'); % This should take several minutes to compute

% Proposals is the ranked list of object proposals, from highest rank(1) to lowest rank (length of list)
% Each proposal is represented by the list of superpixels belonging to that region
% The "superpixels" variable gives the pixel map of the superpixel labels
% You can display a proposal using:
imagesc(ismember(superpixels, proposals{1}));

% Further information, such as the actual occlusion boundary and geometric context output
% can be found in the third output: computed_data
[proposals superpixels computed_data] = generate_proposals('proposals/car.jpg');