The class implements the modified H. Hirschmuller algorithm [HH08] that differs from the original one as follows: [詳解]
#include <calib3d.hpp>
cv::StereoMatcherを継承しています。
公開型 | |
| enum | { MODE_SGBM = 0 , MODE_HH = 1 , MODE_SGBM_3WAY = 2 , MODE_HH4 = 3 } |
 基底クラス cv::StereoMatcher に属する継承公開型 | |
| enum | { DISP_SHIFT = 4 , DISP_SCALE = (1 << DISP_SHIFT) } |
公開メンバ関数 | |
| virtual CV_WRAP int | getPreFilterCap () const =0 |
| virtual CV_WRAP void | setPreFilterCap (int preFilterCap)=0 |
| virtual CV_WRAP int | getUniquenessRatio () const =0 |
| virtual CV_WRAP void | setUniquenessRatio (int uniquenessRatio)=0 |
| virtual CV_WRAP int | getP1 () const =0 |
| virtual CV_WRAP void | setP1 (int P1)=0 |
| virtual CV_WRAP int | getP2 () const =0 |
| virtual CV_WRAP void | setP2 (int P2)=0 |
| virtual CV_WRAP int | getMode () const =0 |
| virtual CV_WRAP void | setMode (int mode)=0 |
| 基底クラス cv::StereoMatcher に属する継承公開メンバ関数 | |
| virtual CV_WRAP void | compute (InputArray left, InputArray right, OutputArray disparity)=0 |
| Computes disparity map for the specified stereo pair [詳解] | |
| virtual CV_WRAP int | getMinDisparity () const =0 |
| virtual CV_WRAP void | setMinDisparity (int minDisparity)=0 |
| virtual CV_WRAP int | getNumDisparities () const =0 |
| virtual CV_WRAP void | setNumDisparities (int numDisparities)=0 |
| virtual CV_WRAP int | getBlockSize () const =0 |
| virtual CV_WRAP void | setBlockSize (int blockSize)=0 |
| virtual CV_WRAP int | getSpeckleWindowSize () const =0 |
| virtual CV_WRAP void | setSpeckleWindowSize (int speckleWindowSize)=0 |
| virtual CV_WRAP int | getSpeckleRange () const =0 |
| virtual CV_WRAP void | setSpeckleRange (int speckleRange)=0 |
| virtual CV_WRAP int | getDisp12MaxDiff () const =0 |
| virtual CV_WRAP void | setDisp12MaxDiff (int disp12MaxDiff)=0 |
| 基底クラス cv::Algorithm に属する継承公開メンバ関数 | |
| virtual CV_WRAP void | clear () |
| Clears the algorithm state [詳解] | |
| virtual void | write (FileStorage &fs) const |
| Stores algorithm parameters in a file storage [詳解] | |
| CV_WRAP void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
| simplified API for language bindings これはオーバーロードされたメンバ関数です。利便性のために用意されています。元の関数との違いは引き数のみです。 | |
| virtual CV_WRAP void | read (const FileNode &fn) |
| Reads algorithm parameters from a file storage [詳解] | |
| virtual CV_WRAP bool | empty () const |
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read [詳解] | |
| virtual CV_WRAP void | save (const String &filename) const |
| virtual CV_WRAP String | getDefaultName () const |
静的公開メンバ関数 | |
| static CV_WRAP Ptr< StereoSGBM > | create (int minDisparity=0, int numDisparities=16, int blockSize=3, int P1=0, int P2=0, int disp12MaxDiff=0, int preFilterCap=0, int uniquenessRatio=0, int speckleWindowSize=0, int speckleRange=0, int mode=StereoSGBM::MODE_SGBM) |
| Creates StereoSGBM object [詳解] | |
| 基底クラス cv::Algorithm に属する継承静的公開メンバ関数 | |
| template<typename _Tp > | |
| static Ptr< _Tp > | read (const FileNode &fn) |
| Reads algorithm from the file node [詳解] | |
| template<typename _Tp > | |
| static Ptr< _Tp > | load (const String &filename, const String &objname=String()) |
| Loads algorithm from the file [詳解] | |
| template<typename _Tp > | |
| static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String()) |
| Loads algorithm from a String [詳解] | |
その他の継承メンバ | |
| 基底クラス cv::Algorithm に属する継承限定公開メンバ関数 | |
| void | writeFormat (FileStorage &fs) const |
詳解
The class implements the modified H. Hirschmuller algorithm [HH08] 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 [BT98] 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).
- 覚え書き
- (Python) An example illustrating the use of the StereoSGBM matching algorithm can be found at opencv_source_code/samples/python/stereo_match.py
関数詳解
◆ create()
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static |
Creates StereoSGBM object
- 引数
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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. See below. P2 The second parameter controlling the disparity smoothness. 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*blockSize*blockSize and 32*number_of_image_channels*blockSize*blockSize , 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.
このクラス詳解は次のファイルから抽出されました:
