Code used in the paper "SHED: Shape Edit Distance for Fine-grained Shape Similarity", SIGGRAPH ASIA 2015
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% ------------------------------------------------------------------------ % SHED: Shape Edit Distance for Fine-grained Shape Similarity % Yanir Kleiman, Oliver van Kaick, Olga Sorkine-Hornung, Daniel Cohen-Or % SIGGRAPH ASIA 2015 % ------------------------------------------------------------------------ % % This code computes Shape Edit Distance (SHED) % for a collection of segmented shapes. % It is well documented, so feel free to take a look inside. % % First, add the folder 'Descs' and its subfolder into the path. % The starting point is the function ShedFromList. % I attached 7 vases as an example to get you going. % To test SHED on those vases, run the following command: [shed, Matchings, Shapes, shape_files] = ShedFromList('list.txt'); % You can use the output values to further experiment with the system, % for example by changing the weights, providing a manual matching, etc. % % The most important part of the code is: % MatchShapes.m: The adaptive spectral matching algorithm described in the paper. % ShedFromMatching.m: Computes SHED from loaded segmented shapes with a given matching. % % To render the results, use the following code: RenderMatchingFigure(Shapes, Matchings, 'test', 1:7, 'testdata'); % It renders and saves a figure for each shape. The segments are color % coded to match the first shape in the list (in this case, shape #1). % The figures are saved in the folder 'data' (the last parameter). % Look inside the function to see more options. % % To segment shapes using approximately convex segmentation, see here: % http://www.cs.tau.ac.il/~noafish/wcseg/ % %%% Copyright (c) 2015 Yanir Kleiman <yanirk@gmail.com>
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Code used in the paper "SHED: Shape Edit Distance for Fine-grained Shape Similarity", SIGGRAPH ASIA 2015
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