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| SOURCE README FOR AUTOMATIC PHOTO POPUP AND GEOMETRIC CONTEXT |
| Derek Hoiem (dhoiem@cs.cmu.edu) |
| 01/08/2010 |
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| LICENSE |
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| Copyright (C) 2007 Derek Hoiem, Carnegie Mellon University |
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| This software is available for only non-commercial use. See the attached |
| license in LICENSE.txt. |
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| REFERENCES |
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| This code implements the following papers. Note that the implementation may not be exact. |
| Please cite one or more of these papers, depending on the use. |
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| D. Hoiem, A.A. Efros, and M. Hebert, "Geometric Context from a Single Image", ICCV 2005. |
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| D. Hoiem, A.A. Efros, and M. Hebert, "Recovering Surface Layout from an Image", IJCV, Vol. 75, No. 1, |
| October 2007. |
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| D. Hoiem, A.A. Efros, and M. Hebert, "Automatic Photo Pop-up", ACM SIGGRAPH 2005. |
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| Note about VERSIONS |
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| This contains two versions of the "Automatic Photo Pop-up" and "Geometric |
| "Context" code. The first version is from the SIGGRAPH 2005 / ICCV 2005 papers |
| and involves the functions photoPopup and APPtestImage. The second version |
| is from the IJCV 2007 paper and involves the functions photoPopupIjcv and |
| ijcvTestImage. Note that these implementations may not be exact. In particular, |
| some changes to features were made to improve speed, which may have small effects |
| on accuracy. Further, the multiple segmentation algorithm is random, so different |
| runs will not produce identical results. |
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| How to RUN: |
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| First, appropriately replace the path for the segment command in im2superpixels.m. |
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| Geometric Context version 1 (ICCV 2005): |
| [labels, conf_map, maps, pmaps] = APPtestImage(image, imsegs, vClassifier, hClassifier, segDensity) |
| image should be a double color image |
| imsegs is the superpixel structure (if empty, will be computed) |
| The remaining three arguments are stored in data/classifiers_08_22_2005.mat |
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| [labels, conf_map, imsegs] = ... |
| APPtestDirectory(segDensity, vClassifier, hClassifier, imdir, imfn, varargin) |
| Processes a directory of images with given filenames. Optional last argument is where to |
| store displayed results. |
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| Geometric Context version 2 (IJCV 2007): |
| [pg, data, imsegs] = ijcvTestImage(im, imsegs, classifiers, smaps, spdata, adjlist, edata); |
| The only required fields are im and classifiers. |
| Example usage: |
| load '../data/ijcvClassifier.mat' |
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| classifiers=load('../data/ijcvClassifier_indoor.mat'); |
| [pg, data, imsegs] = ijcvTestImage(im, [], classifiers); |
| [cimages, cnames] = pg2confidenceImages(imsegs, {pg}); |
| % only keep ground pourous sky vertical [1 5 7 8] |
| geom_c_map = cimages{1}(:,:,[1 5 7 8]); |
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| Classifiers trained on indoor and outdoor images are provided in the data directory. |
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| [pg, smaps, imsegs] = ijcvTestImageList(fn, imsegs, classifiers, laboutdir, confoutdir) |
| Processes all images whose names are given in fn. As above, imsegs can be empty. |
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| Automatic Photo Pop-up (SIGGRAPH 2005, IJCV 2007) |
| photoPopup(fnData, fnImage, extSuperpixelImage, outdir) |
| This is the 2005 version. |
| fnData is the filename containing the classifiers (data/classifiers_08_22_2005.mat). |
| If extSuperpixelImage is empty, it will be computed. |
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| photoPopupIjcv(fnData, fnImage, extSuperpixelImage, outdir) |
| This is the IJCV 2007 version. See notes above. |
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| Training: |
| For the IJCV version, see src/ijcv06/ijcvMultiSegScript.m |
| This function performs both training and evaluation. It requires some edits. It is currently |
| setup for cross-validation, but it should be straightforward to use separate train and test sets. |
| The Geometric Context Dataset (separate download) contains rand_indices which specifies the |
| train/test splits. |
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| Other useful functions: |
| src/util/splitpg.m |
| src/util/pg2confidenceImages.m |
| src/util/pg2* |
| src/util/write* |
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| NOTES: |
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| Superpixels: |
| I use the segmentation code provided by Felzenszwalb and Huttenlocher |
| at people.cs.uchicago.edu/~pff/segment/ to create the superpixels in my |
| experiments. The first three arguments (sigma, k, min) that I use are |
| 0.8 100 100. I've included a pl script for segmenting a directory |
| that you may find useful. You can also use a different program to create |
| the superpixel image. That image should have a different RGB color for |
| each segment without drawn boundaries between segments. |
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| (C) Derek Hoiem, Carnegie Mellon University, 2007 |
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