cv::stereo::QuasiDenseStereo Class Reference

Class containing the methods needed for Quasi Dense Stereo computation. More...

#include <opencv2/xstereo/quasi_dense_stereo.hpp>

Collaboration diagram for cv::stereo::QuasiDenseStereo:

Public Member Functions
virtual	~QuasiDenseStereo ()=0
	destructor Method to free all the memory allocated by matrices and vectors in this class.
virtual void	getDenseMatches (std::vector< MatchQuasiDense > &denseMatches)=0
	Get The dense corresponding points.
virtual cv::Mat	getDisparity ()=0
	Compute and return the disparity map based on the correspondences found in the "process" method.
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.
virtual void	getSparseMatches (std::vector< MatchQuasiDense > &sMatches)=0
	Get The sparse corresponding points.
virtual int	loadParameters (cv::String filepath)=0
	Load a file containing the configuration parameters of the class.
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.
virtual int	saveParameters (cv::String filepath)=0
	Save a file containing all the configuration parameters the class is currently set to.

Static Public Member Functions
static cv::Ptr< QuasiDenseStereo >	create (cv::Size monoImgSize, cv::String paramFilepath=cv::String())

Public Attributes
PropagationParameters	Param

Detailed Description

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 [254]. If this code is useful for your work please cite [254].

Also the original growing scheme idea is described in [160]

Constructor & Destructor Documentation

~QuasiDenseStereo()

virtual cv::stereo::QuasiDenseStereo::~QuasiDenseStereo ( )

pure virtual

destructor Method to free all the memory allocated by matrices and vectors in this class.

Member Function Documentation

create()

static cv::Ptr< QuasiDenseStereo > cv::stereo::QuasiDenseStereo::create ( cv::Size monoImgSize, cv::String paramFilepath = cv::String() )

static

Python:
	cv.stereo.QuasiDenseStereo.create(	monoImgSize[, paramFilepath]	) ->	retval
	cv.stereo.QuasiDenseStereo_create(	monoImgSize[, paramFilepath]	) ->	retval

getDenseMatches()

virtual void cv::stereo::QuasiDenseStereo::getDenseMatches ( std::vector< MatchQuasiDense > & denseMatches )

pure virtual

Python:
	cv.stereo.QuasiDenseStereo.getDenseMatches(		) ->	denseMatches

Get The dense corresponding points.

Parameters

[out]

denseMatches

A vector containing all dense matches.

Note

The method clears the denseMatches vector.

The returned Match elements inside the sMatches vector, do not use corr member.

getDisparity()

virtual cv::Mat cv::stereo::QuasiDenseStereo::getDisparity ( )

pure virtual

Python:
	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

quantizeDisparity

getMatch()

virtual cv::Point2f cv::stereo::QuasiDenseStereo::getMatch ( const int x, const int y )

pure virtual

Python:
	cv.stereo.QuasiDenseStereo.getMatch(	x, y	) ->	retval

Specify pixel coordinates in the left image and get its corresponding location in the right image.

Parameters

[in]	x	The x pixel coordinate in the left image channel.
[in]	y	The y pixel coordinate in the left image channel.

Return values

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 ( std::vector< MatchQuasiDense > & sMatches )

pure virtual

Python:
	cv.stereo.QuasiDenseStereo.getSparseMatches(		) ->	sMatches

Get The sparse corresponding points.

Parameters

[out]

sMatches

A vector containing all sparse correspondences.

Note

The method clears the sMatches vector.

The returned Match elements inside the sMatches vector, do not use corr member.

loadParameters()

virtual int cv::stereo::QuasiDenseStereo::loadParameters ( cv::String filepath )

pure virtual

Python:
	cv.stereo.QuasiDenseStereo.loadParameters(	filepath	) ->	retval

Load a file containing the configuration parameters of the class.

Parameters

[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

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.

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 ( const cv::Mat & imgLeft, const cv::Mat & imgRight )

pure virtual

Python:
	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

[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

quasiDenseMatching

saveParameters()

virtual int cv::stereo::QuasiDenseStereo::saveParameters ( cv::String filepath )

pure virtual

Python:
	cv.stereo.QuasiDenseStereo.saveParameters(	filepath	) ->	retval

Save a file containing all the configuration parameters the class is currently set to.

Parameters

[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.

This method can be used to generate a template file for tuning the class.

See also

loadParameters

Member Data Documentation

Param

PropagationParameters cv::stereo::QuasiDenseStereo::Param

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The documentation for this class was generated from the following file:

• opencv2/xstereo/quasi_dense_stereo.hpp