The class implements the modified H. Hirschmuller algorithm [126] that differs from the original one as follows:
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#include <opencv2/xstereo.hpp>
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| static Ptr< StereoBinarySGBM > | create (int minDisparity, int numDisparities, int blockSize, int P1=100, int P2=1000, int disp12MaxDiff=1, int preFilterCap=0, int uniquenessRatio=5, int speckleWindowSize=400, int speckleRange=200, int mode=StereoBinarySGBM::MODE_SGBM) |
| | Creates StereoSGBM object.
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| static Ptr< _Tp > | load (const String &filename, const String &objname=String()) |
| | Loads algorithm from the file.
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| static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String()) |
| | Loads algorithm from a String.
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| static Ptr< _Tp > | read (const FileNode &fn) |
| | Reads algorithm from the file node.
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The class implements the modified H. Hirschmuller algorithm [126] that differs from the original one as follows:
- By default, the algorithm is single-pass, which means that you consider only 5 directions instead of 8. Set mode=StereoSGBM::MODE_HH in createStereoSGBM to run the full variant of the algorithm but beware that it may consume a lot of memory.
- The algorithm matches blocks, not individual pixels. Though, setting blockSize=1 reduces the blocks to single pixels.
- Mutual information cost function is not implemented. Instead, a simpler Birchfield-Tomasi sub-pixel metric from [28] is used. Though, the color images are supported as well.
- Some pre- and post- processing steps from K. Konolige algorithm StereoBM are included, for example: pre-filtering (StereoBM::PREFILTER_XSOBEL type) and post-filtering (uniqueness check, quadratic interpolation and speckle filtering).
- Note
- (Python) An example illustrating the use of the StereoSGBM matching algorithm can be found at opencv_source_code/samples/python2/stereo_match.py
◆ anonymous enum
| Enumerator |
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| MODE_SGBM | |
| MODE_HH | |
◆ create()
| static Ptr< StereoBinarySGBM > cv::stereo::StereoBinarySGBM::create |
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int | minDisparity, |
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int | numDisparities, |
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int | blockSize, |
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int | P1 = 100, |
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int | P2 = 1000, |
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int | disp12MaxDiff = 1, |
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int | preFilterCap = 0, |
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int | uniquenessRatio = 5, |
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int | speckleWindowSize = 400, |
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int | speckleRange = 200, |
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int | mode = StereoBinarySGBM::MODE_SGBM ) |
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static |
Creates StereoSGBM object.
- Parameters
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| minDisparity | Minimum possible disparity value. Normally, it is zero but sometimes rectification algorithms can shift images, so this parameter needs to be adjusted accordingly. |
| numDisparities | Maximum disparity minus minimum disparity. The value is always greater than zero. In the current implementation, this parameter must be divisible by 16. |
| blockSize | Matched block size. It must be an odd number >=1 . Normally, it should be somewhere in the 3..11 range. |
| P1 | The first parameter controlling the disparity smoothness.This parameter is used for the case of slanted surfaces (not fronto parallel). |
| P2 | The second parameter controlling the disparity smoothness.This parameter is used for "solving" the depth discontinuities problem. The larger the values are, the smoother the disparity is. P1 is the penalty on the disparity change by plus or minus 1 between neighbor pixels. P2 is the penalty on the disparity change by more than 1 between neighbor pixels. The algorithm requires P2 > P1 . See stereo_match.cpp sample where some reasonably good P1 and P2 values are shown (like 8*number_of_image_channels*SADWindowSize*SADWindowSize and 32*number_of_image_channels*SADWindowSize*SADWindowSize , respectively). |
| disp12MaxDiff | Maximum allowed difference (in integer pixel units) in the left-right disparity check. Set it to a non-positive value to disable the check. |
| preFilterCap | Truncation value for the prefiltered image pixels. The algorithm first computes x-derivative at each pixel and clips its value by [-preFilterCap, preFilterCap] interval. The result values are passed to the Birchfield-Tomasi pixel cost function. |
| uniquenessRatio | Margin in percentage by which the best (minimum) computed cost function value should "win" the second best value to consider the found match correct. Normally, a value within the 5-15 range is good enough. |
| speckleWindowSize | Maximum size of smooth disparity regions to consider their noise speckles and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the 50-200 range. |
| speckleRange | Maximum disparity variation within each connected component. If you do speckle filtering, set the parameter to a positive value, it will be implicitly multiplied by 16. Normally, 1 or 2 is good enough. |
| mode | Set it to StereoSGBM::MODE_HH to run the full-scale two-pass dynamic programming algorithm. It will consume O(W*H*numDisparities) bytes, which is large for 640x480 stereo and huge for HD-size pictures. By default, it is set to false . |
The first constructor initializes StereoSGBM with all the default parameters. So, you only have to set StereoSGBM::numDisparities at minimum. The second constructor enables you to set each parameter to a custom value.
◆ getBinaryKernelType()
| virtual int cv::stereo::StereoBinarySGBM::getBinaryKernelType |
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const |
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◆ getMode()
| virtual int cv::stereo::StereoBinarySGBM::getMode |
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const |
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pure virtual |
◆ getP1()
| virtual int cv::stereo::StereoBinarySGBM::getP1 |
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const |
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pure virtual |
◆ getP2()
| virtual int cv::stereo::StereoBinarySGBM::getP2 |
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const |
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pure virtual |
◆ getPreFilterCap()
| virtual int cv::stereo::StereoBinarySGBM::getPreFilterCap |
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const |
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pure virtual |
◆ getSpekleRemovalTechnique()
| virtual int cv::stereo::StereoBinarySGBM::getSpekleRemovalTechnique |
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const |
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pure virtual |
◆ getSubPixelInterpolationMethod()
| virtual int cv::stereo::StereoBinarySGBM::getSubPixelInterpolationMethod |
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const |
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pure virtual |
◆ getUniquenessRatio()
| virtual int cv::stereo::StereoBinarySGBM::getUniquenessRatio |
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const |
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pure virtual |
◆ setBinaryKernelType()
| virtual void cv::stereo::StereoBinarySGBM::setBinaryKernelType |
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int | value | ) |
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pure virtual |
◆ setMode()
| virtual void cv::stereo::StereoBinarySGBM::setMode |
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int | mode | ) |
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pure virtual |
◆ setP1()
| virtual void cv::stereo::StereoBinarySGBM::setP1 |
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int | P1 | ) |
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pure virtual |
◆ setP2()
| virtual void cv::stereo::StereoBinarySGBM::setP2 |
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int | P2 | ) |
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pure virtual |
◆ setPreFilterCap()
| virtual void cv::stereo::StereoBinarySGBM::setPreFilterCap |
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int | preFilterCap | ) |
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pure virtual |
◆ setSpekleRemovalTechnique()
| virtual void cv::stereo::StereoBinarySGBM::setSpekleRemovalTechnique |
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int | factor | ) |
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pure virtual |
◆ setSubPixelInterpolationMethod()
| virtual void cv::stereo::StereoBinarySGBM::setSubPixelInterpolationMethod |
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int | value | ) |
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pure virtual |
◆ setUniquenessRatio()
| virtual void cv::stereo::StereoBinarySGBM::setUniquenessRatio |
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int | uniquenessRatio | ) |
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pure virtual |
The documentation for this class was generated from the following file:
Public Types inherited from cv::StereoMatcher
1.12.0