Cross-Scale Cost Aggregation for Stereo Matching (CVPR 2014)
================
## Compilation
### Windows
The code is a Visual Studio 2010 project on Windows x64 platform. To build the project, you need to configure [OpenCV](http://opencv.org/) on your own PC. (version 2.4.6, however, other versions are acceptable by modifying [CommFunc.h](/SSCA/CommFunc.h)).
### Other Platforms
The code requires no platform-dependent libraries. Thus, it is easy to compile it on other platforms with OpenCV.
## Usage
Run the program with the following paramters:
`Usage: [CC_METHOD] [CA_METHOD] [PP_METHOD] [C_ALPHA] [lImg] [rImg] [lDis] [maxDis] [disSc]`
- `[CC_METHOD]` -- cost computation methods, currently support:
- `GRD` -- [intensity + gradient](#GF)
- `CEN` -- [Census Transform](#CT)
- `CG` -- Census + gradient
- `[CA_METHOD]` -- cost aggregation methods, currently support:
- `GF` -- [guided image filter](#GF)
- `BF` -- [bilateral filter](#BF)
- `BOX` -- box filter
- `NL` -- [non-local cost aggregation](#NL)
- `ST` -- [segment-tree cost aggregation](#ST)
- `[PP_METHOD]` -- post processing methods, currently support:
- `WM` -- [weighted median filtering](#GF)
- `SG` -- segment based (experimental)
- `[C_ALPHA]` -- regularization paramter, i.e. `$\lambda$` in the paper.
- `[lImg]` -- input left color image file name. (all formats supported by OpenCV)
- `[rImg]` -- input right color image file name.
- `[lDis]` -- output left disparity map file name.
- `[maxDis]` -- maximum disparity range, e.g. `60` for Middlebury and `256` for KITTI dataets.
- `[disSc]` -- scale disparity, e.g. `4` for Middlebury and `1` for KITTI datasets.
**Hint**: to enable post-processing, you must uncomment `// #define COMPUTE_RIGHT` in [CommFunc.h](/SSCA/CommFunc.h) to allow computing right disparity map.
## Citation
Citation is very important for researchers. If you find this code useful, please cite:
```
@inproceedings{CrossScaleStereo,
author = {Kang Zhang and Yuqiang Fang and Dongbo Min and Lifeng Sun and Shiqiang Yang and Shuicheng Yan and Qi Tian},
title = {Cross-Scale Cost Aggregation for Stereo Matching},
booktitle = {CVPR},
year = {2014}
}
```
Since some cost aggregation methods ([GF](#GF), [NL](#NL), [ST](#ST)) are built uppon other papers' code, you also need to cite corresponding papers as listed below.
## Reference
<a name="CT">[CT]</a>: R. Zabih and J. Woodfill. Non-parametric local transforms for computing visual correspondence. In ECCV, 1994
<a name="GF">[GF]</a>: C. Rhemann, A. Hosni, M. Bleyer, C. Rother, and M. Gelautz. Fast cost-volume filtering for visual correspondence and beyond. In CVPR, 2011
<a name="ST">[ST]</a>: X. Mei, X. Sun, W. Dong, H. Wang, and X. Zhang. Segment-tree based cost aggregation for stereo matching. In CVPR, 2013
<a name="BF">[BF]</a>: K.-J. Yoon and I. S. Kweon. Adaptive support-weight approach for correspondence search. TPAMI, 2006
<a name="NL">[NL]</a>: Q. Yang. A non-local cost aggregation method for stereo matching. In CVPR, 2012
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CrossScale Stereo
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CrossScaleStereo-master.zip (71个子文件)
CrossScaleStereo-master
.gitignore 2KB
.tfignore 5B
README.md 3KB
SSCA.sln 1KB
SSCA
main.cpp 13KB
CCMethod.h 709B
SSCA.cpp 11KB
GetMehod.h 1KB
CAST
Toolkit.h 4KB
ctmf.h 1KB
Toolkit.cpp 2KB
StereoHelper.h 2KB
STCA.cpp 2KB
SegmentTree.h 3KB
StereoDisparity.h 4KB
SegmentTree.cpp 7KB
disjoint-set.h 2KB
STCA.h 420B
ctmf.c 15KB
StereoHelper.cpp 8KB
StereoDisparity.cpp 6KB
segment-graph.h 2KB
CC
CenCC.cpp 4KB
CenCC.h 484B
GrdCC.cpp 4KB
GrdCC.h 553B
CGCC.cpp 5KB
CGCC.h 626B
PPMethod.h 695B
CANLC
ctmf.h 265B
qx_nonlocal_cost_aggregation.cpp 8KB
qx_mst_kruskals_image.cpp 9KB
NLCCA.cpp 2KB
qx_tree_filter.cpp 4KB
qx_nonlocal_cost_aggregation.h 2KB
qx_basic.h 13KB
qx_mst_kruskals_image.h 2KB
ctmf.c 15KB
NLCCA.h 415B
qx_basic.cpp 17KB
qx_tree_filter.h 1KB
SSCA.vcxproj.filters 7KB
SSCA.h 1KB
SSCA.vcxproj 10KB
CAMethod.h 586B
CAFilter
BoxCA.h 331B
GFCA.h 331B
BFCA.cpp 324B
GFCA.cpp 277B
BilateralFilter.cpp 3KB
BoxCA.cpp 295B
GuidedFilter.cpp 8KB
GuidedFilter.h 895B
BilateralFilter.h 181B
BFCA.h 340B
PPSG
pnmfile.h 5KB
image.h 2KB
filter.h 3KB
SGPP.h 618B
imutil.h 2KB
SGPP.cpp 19KB
misc.h 2KB
imconv.h 5KB
segment-image.h 4KB
disjoint-set.h 2KB
segment-graph.h 2KB
convolve.h 2KB
CommFunc.h 2KB
PPWM
WMPP.h 433B
WMPP.cpp 9KB
LICENSE 18KB
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