Class containing the methods needed for Quasi Dense Stereo computation.
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#include <opencv2/stereo/quasi_dense_stereo.hpp>
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| virtual | ~QuasiDenseStereo ()=0 |
| | destructor Method to free all the memory allocated by matrices and vectors in this class.
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| virtual void | getDenseMatches (std::vector< MatchQuasiDense > &denseMatches)=0 |
| | Get The dense corresponding points.
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| virtual cv::Mat | getDisparity ()=0 |
| | Compute and return the disparity map based on the correspondences found in the "process" method.
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| virtual cv::Point2f | getMatch (const int x, const int y)=0 |
| | Specify pixel coordinates in the left image and get its corresponding location in the right image.
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| virtual void | getSparseMatches (std::vector< MatchQuasiDense > &sMatches)=0 |
| | Get The sparse corresponding points.
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| virtual int | loadParameters (cv::String filepath)=0 |
| | Load a file containing the configuration parameters of the class.
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| virtual void | process (const cv::Mat &imgLeft, const cv::Mat &imgRight)=0 |
| | Main process of the algorithm. This method computes the sparse seeds and then densifies them.
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| virtual int | saveParameters (cv::String filepath)=0 |
| | Save a file containing all the configuration parameters the class is currently set to.
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Class containing the methods needed for Quasi Dense Stereo computation.
This module contains the code to perform quasi dense stereo matching. The method initially starts with a sparse 3D reconstruction based on feature matching across a stereo image pair and subsequently propagates the structure into neighboring image regions. To obtain initial seed correspondences, the algorithm locates Shi and Tomashi features in the left image of the stereo pair and then tracks them using pyramidal Lucas-Kanade in the right image. To densify the sparse correspondences, the algorithm computes the zero-mean normalized cross-correlation (ZNCC) in small patches around every seed pair and uses it as a quality metric for each match. In this code, we introduce a custom structure to store the location and ZNCC value of correspondences called "Match". Seed Matches are stored in a priority queue sorted according to their ZNCC value, allowing for the best quality Match to be readily available. The algorithm pops Matches and uses them to extract new matches around them. This is done by considering a small neighboring area around each Seed and retrieving correspondences above a certain texture threshold that are not previously computed. New matches are stored in the seed priority queue and used as seeds. The propagation process ends when no additional matches can be retrieved.
- See also
- This code represents the work presented in [259]. If this code is useful for your work please cite [259].
Also the original growing scheme idea is described in [165]
◆ ~QuasiDenseStereo()
| virtual cv::stereo::QuasiDenseStereo::~QuasiDenseStereo |
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pure virtual |
destructor Method to free all the memory allocated by matrices and vectors in this class.
◆ create()
| Python: |
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| cv.stereo.QuasiDenseStereo.create( | monoImgSize[, paramFilepath] | ) -> | retval |
| cv.stereo.QuasiDenseStereo_create( | monoImgSize[, paramFilepath] | ) -> | retval |
◆ getDenseMatches()
| virtual void cv::stereo::QuasiDenseStereo::getDenseMatches |
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std::vector< MatchQuasiDense > & | denseMatches | ) |
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pure virtual |
| Python: |
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| cv.stereo.QuasiDenseStereo.getDenseMatches( | | ) -> | denseMatches |
Get The dense corresponding points.
- Parameters
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| [out] | denseMatches | A vector containing all dense matches. |
- Note
- The method clears the denseMatches vector.
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The returned Match elements inside the sMatches vector, do not use corr member.
◆ getDisparity()
| virtual cv::Mat cv::stereo::QuasiDenseStereo::getDisparity |
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pure virtual |
| Python: |
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| cv.stereo.QuasiDenseStereo.getDisparity( | | ) -> | retval |
Compute and return the disparity map based on the correspondences found in the "process" method.
- Note
- Default level is 50
- Returns
- cv::Mat containing a the disparity image in grayscale.
- See also
- computeDisparity
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quantizeDisparity
◆ getMatch()
| virtual cv::Point2f cv::stereo::QuasiDenseStereo::getMatch |
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const int | x, |
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const int | y ) |
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pure virtual |
| Python: |
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| cv.stereo.QuasiDenseStereo.getMatch( | x, y | ) -> | retval |
Specify pixel coordinates in the left image and get its corresponding location in the right image.
- Parameters
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| [in] | x | The x pixel coordinate in the left image channel. |
| [in] | y | The y pixel coordinate in the left image channel. |
- Return values
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| cv::Point(x,y) | The location of the corresponding pixel in the right image. |
| cv::Point(0,0) | (NO_MATCH) if no match is found in the right image for the specified pixel location in the left image. |
- Note
- This method should be always called after process, otherwise the matches will not be correct.
◆ getSparseMatches()
| virtual void cv::stereo::QuasiDenseStereo::getSparseMatches |
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std::vector< MatchQuasiDense > & | sMatches | ) |
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pure virtual |
| Python: |
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| cv.stereo.QuasiDenseStereo.getSparseMatches( | | ) -> | sMatches |
Get The sparse corresponding points.
- Parameters
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| [out] | sMatches | A vector containing all sparse correspondences. |
- Note
- The method clears the sMatches vector.
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The returned Match elements inside the sMatches vector, do not use corr member.
◆ loadParameters()
| virtual int cv::stereo::QuasiDenseStereo::loadParameters |
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cv::String | filepath | ) |
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pure virtual |
| Python: |
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| cv.stereo.QuasiDenseStereo.loadParameters( | filepath | ) -> | retval |
Load a file containing the configuration parameters of the class.
- Parameters
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| [in] | filepath | The location of the .YAML file containing the configuration parameters. |
- Note
- default value is an empty string in which case the default parameters will be loaded.
- Return values
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| 1 | If the path is not empty and the program loaded the parameters successfully. |
| 0 | If the path is empty and the program loaded default parameters. |
| -1 | If the file location is not valid or the program could not open the file and loaded default parameters from defaults.hpp. |
- Note
- The method is automatically called in the constructor and configures the class.
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Loading different parameters will have an effect on the output. This is useful for tuning in case of video processing.
- See also
- loadParameters
◆ process()
| virtual void cv::stereo::QuasiDenseStereo::process |
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const cv::Mat & | imgLeft, |
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const cv::Mat & | imgRight ) |
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pure virtual |
| Python: |
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| cv.stereo.QuasiDenseStereo.process( | imgLeft, imgRight | ) -> | None |
Main process of the algorithm. This method computes the sparse seeds and then densifies them.
Initially input images are converted to gray-scale and then the sparseMatching method is called to obtain the sparse stereo. Finally quasiDenseMatching is called to densify the corresponding points.
- Parameters
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| [in] | imgLeft | The left Channel of a stereo image pair. |
| [in] | imgRight | The right Channel of a stereo image pair. |
- Note
- If input images are in color, the method assumes that are BGR and converts them to grayscale.
- See also
- sparseMatching
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quasiDenseMatching
◆ saveParameters()
| virtual int cv::stereo::QuasiDenseStereo::saveParameters |
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cv::String | filepath | ) |
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pure virtual |
| Python: |
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| cv.stereo.QuasiDenseStereo.saveParameters( | filepath | ) -> | retval |
Save a file containing all the configuration parameters the class is currently set to.
- Parameters
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| [in] | filepath | The location to store the parameters file. |
- Note
- Calling this method with no arguments will result in storing class parameters to a file names "qds_parameters.yaml" in the root project folder.
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This method can be used to generate a template file for tuning the class.
- See also
- loadParameters
◆ Param
The documentation for this class was generated from the following file:
1.16.1