文件列表:

148089.jpg (96491, 2015-08-19)
242078.jpg (83046, 2015-08-19)
demo.m (4012, 2017-12-16)
demoERS.py (692, 2015-08-19)
ERS (0, 2018-05-21)
ERS\Edge.h (2031, 2015-08-19)
ERS\Image.h (4003, 2015-08-19)
ERS\ImageIO.h (6173, 2015-08-19)
ERS\MERCCInput.cpp (2127, 2015-08-19)
ERS\MERCClustering.h (1849, 2015-08-19)
ERS\MERCDisjointSet.cpp (2299, 2015-08-19)
ERS\MERCDisjointSet.h (1911, 2015-08-19)
ERS\MERCEdge.h (2458, 2015-08-19)
ERS\MERCFunctions.cpp (3079, 2015-08-19)
ERS\MERCFunctions.h (2029, 2015-08-19)
ERS\MERCInput.h (1418, 2015-08-19)
ERS\MERCInputImage.h (2955, 2015-08-19)
ERS\MERCLazyGreedy.cpp (3761, 2015-08-19)
ERS\MERCLazyGreedy.h (1337, 2015-08-19)
ERS\MERCOutput.cpp (1880, 2015-08-19)
ERS\MERCOutput.h (1426, 2015-08-19)
ERS\MERCOutputImage.h (1854, 2015-08-19)
ERS\mex_ers.cpp (4944, 2015-08-19)
ERS\MHeap.h (6310, 2015-08-19)
ERS\MList.h (3145, 2015-08-19)
ERS\MMFunctions.h (5560, 2015-08-19)
ERS\MSubmodularHeap.h (4224, 2015-08-19)
erspy.exp (599, 2015-08-19)
erspy.lib (1682, 2015-08-19)
erspy.pdb (1617920, 2015-08-19)
erspy.pyd (45056, 2015-08-19)
make.m (361, 2015-08-19)
mex_ers.mexw64 (28160, 2015-08-19)
random_color.m (682, 2015-08-19)
seg2bmap.m (1300, 2015-08-19)
vc (0, 2018-05-21)
vc\ers.sln (1309, 2015-08-19)
vc\ers.v12.suo (17920, 2015-08-19)
... ...

/******************************************************************** * Entropy Rate Superpixel Segmentation code * * * * Ming-Yu Liu (UMD), Oncel Tuzel (MERL), * * Srikumar Ramalingam (MERL) and Rama Chellappa (UMD) * * * /******************************************************************** /* Copyright 2011, Ming-Yu Liu All Rights Reserved Permission to use, copy, modify, and distribute this software and its documentation for any non-commercial purpose is hereby granted without fee, provided that the above copyright notice appear in all copies and that both that copyright notice and this permission notice appear in supporting documentation, and that the name of the author not be used in advertising or publicity pertaining to distribution of the software without specific, written prior permission. THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR ANY PARTICULAR PURPOSE. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. */ /******************************************************************** * General information * /******************************************************************** Thanks for your interest in our work. This is a MATLAB wrapper for the Entropy Rate Superpixel Segmentation algorithm. For more detail about the algorithm please refer to the project webpage http://www.umiacs.umd.edu/~mingyliu or the following paper Ming-Yu Liu, Oncel Tuzel, Srikumar Ramalingam, and Rama Chellappa "Entropy Rate Superpixel Segmentation" Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition(CVPR), Colorado Spring, June 2011. If you use this software, you should cite the aforementioned paper in any resulting publication. If you have any questions regarding the code please contact Ming-Yu Liu via . /******************************************************************** * Installation and usage * /******************************************************************** 1) Unzipped the files to $HOME_DIR 2) We have provided pre-compiled mex functions. You may not need to recompile the mex files again. If you need to recompile the codes. In the matlab command prompt, type >>make. This should do the job. 3) Type demo to see a demonstration of the usage of the code. mex_ers.mex : compute the superpixel segmentation for an input image. usage: [labels] = mex_ers(image,nC); [labels] = mex_ers(image,nC,lambda,sigma); [labels] = mex_ers(image,nC,lambda,sigma,conn8); Input: image : the input grey scale image or color image nC : the number of desired superpixels lambda : the balancing parameter ( default = 0.5; ) sigma : the kernel bandwidth ( default = 5.0; ) conn8 : the flag of using 8-connected grid graph structure ( default = 1 ) if set to 0, the algorithm will use 4-connected graph instead. Output: labels : the output image. Each pixel is labeled with the label of the superpixel it belongs to. Note that the labeling begins from 0 to nC-1 /******************************************************************** * Revision History: * /******************************************************************** August 26, 2011; - Fixed two bugs causing compiling errors in Linux environment. August 11, 2011; - Enable the input of color images. August 11, 2011; - Enable the use of 4-connected grid graph structure. July 1, 2011; - First version for the general public

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