* Fixed indexing in prefilter
* Initialised prefilter
* Initialised prefilter with value initialisation
* Added TC to trigger different Mem Allocs in BufferBM
* Optimize cases with only needed conditions
added estimateTranslation3D to calib3d/ptsetreg
* added estimateTranslation3D; follows API and implementation structure for estimateAffine3D, but only allows for translation
* void variables in null function to suppress compiler warnings
* added test for estimateTranslation3D
* changed to Matx13d datatype for translation vector in ptsetreg and test; used short license in test
* removed iostream include
* calib3d: code cleanup
Image sharpness, as well as brightness, are a critical parameter for
accuracte camera calibration. For accessing these parameters for
filtering out problematic calibraiton images, this method calculates
edge profiles by traveling from black to white chessboard cell centers.
Based on this, the number of pixels is calculated required to transit
from black to white. This width of the transition area is a good
indication of how sharp the chessboard is imaged and should be below
~3.0 pixels.
Based on this also motion blur can be detectd by comparing sharpness in
vertical and horizontal direction. All unsharp images should be excluded
from calibration as they will corrupt the calibration result. The same
is true for overexposued images due to a none-linear sensor response.
This can be detected by looking at the average cell brightness of the
detected chessboard.
Lets the user choose the maximum number of iterations the robust
estimator runs for, similary to findHomography. This can significantly
improve performance (at a computational cost).
Changes:
* UMat for blur + rotate resulting in a speedup of around 2X on an i7
* support for boards larger than specified allowing to cover full FOV
* support for markers moving the origin into the center of the board
* increase detection accuracy
The main change is for supporting boards that are larger than the FOV of
the camera and have their origin in the board center. This allows
building OEM calibration targets similar to the one from intel real
sense utilizing corner points as close as possible to the image border.
This is a correction of the previously missleading documentation and a warning related to a common calibration failure described in issue 15992
* corrected incorrect description of failed calibration state.
see issue 15992
* calib3d: apply suggestions from code review by catree
Added type check for solvePnPGeneric | Issue: #16049
* Added type check
* Added checks before type fix
* Tests for 16049
* calib3d: update solvePnP regression check (16049)
Add checks for empty operands in Matrix expressions that don't check properly
* Starting to add checks for empty operands in Matrix expressions that
don't check properly.
* Adding checks and delcarations for checker functions
* Fix signatures and add checks for each class of Matrix Expr operation
* Make it catch the right exception
* Don't expose helper functions to public API
* calib3d: use normalized input in solvePnPGeneric()
* calib3d: java regression test for solvePnPGeneric
* calib3d: python regression test for solvePnPGeneric
(1/4) Revert "Correct image borders and principal point computation in cv::stereoRectify"
This reverts commit 93ff1fb2f2.
(2/4) Revert "fix calib3d changes in 6836 plus some others"
This reverts commit fa42a1cfc2.
(3/4) Revert "fix compiler warning"
This reverts commit b3d55489d3.
(4/4) Revert "add test for 6836"
This reverts commit d06b8c4ea9.
Clarify stereoRectify() doc
The function stereoRectify() takes as input a coordinate transform between two cameras. It is ambiguous how it goes. I clarified that it goes from the second camera to the first.
* Doc bugfix
The documentation page StereoBinaryBM and StereoBinarySGBM says that it returns a disparity that is scaled multiplied by 16. This scaling must be undone before calling reprojectImageTo3D, otherwise the results are wrong. The function reprojectImageTo3D() could do this scaling internally, maybe, but at least the documentation must explain that this has to be done.
* calib3d: update reprojectImageTo3D documentation
* calib3d: add StereoBM/StereoSGBM into notes list
* issue 5769 fixed: cv::stereoRectify fails if given inliers mask of type vector<uchar>
* issue5769 fix using reshape and add regression test
* regression test with outlier detection, testing vector and mat data
* Size comparision of wrong vector within CV_Assert in regression test corrected
* cleanup test code
* Fix for Homogenous precision #14242:
- moved scale computation to an inline function
- use std::numeric_limits<float>::epsilon() instead of != 0.0
* Fix for Homogenous precision #14242:
- fixed warnings for type conversion
* Fix for Homogenous precision #14242:
- use float epsilon() for truncation of doubles
* Fix Issue 13908
Allocate the matrix _Jo only when the solver needs it (ie when solver.state == CvLevMarq::CALC_J)
* Fix calib3D unit test
Fix _Jo allocation when stddev is not empty
* Removing trailing whitespaces
* scope _dp* variables
* fix whitespaces
objectPoints and imagePoints are not checked whether they're empty and
cause checkVector() to fail, thus result in a wrong error message.
Fixes: https://github.com/opencv/opencv/issues/6002
During the cluster-based detection of circle grids, the detected circle
pattern has to be mapped to 3D-points. When doing this the width (i.e.
more circles) and height (i.e. less circles) of the pattern need to
be identified in image coordinates.
Until now this was done by assuming that the shorter side in image
coordinates (length in pixels) corresponds to the height in 3D.
This assumption does not hold if we look at the pattern from
a perspective where the projection of the width is shorter
than the projection of the height. This in turn lead to misdetections in
although the circle pattern was clearly visible.
Instead count how many circles have been detected along two edges of the
projected quadrangle and use the one with more circles as width and the
one with less as height.
* integrated the new C++ persistence; removed old persistence; most of OpenCV compiles fine! the tests have not been run yet
* fixed multiple bugs in the new C++ persistence
* fixed raw size of the parsed empty sequences
* [temporarily] excluded obsolete applications traincascade and createsamples from build
* fixed several compiler warnings and multiple test failures
* undo changes in cocoa window rendering (that was fixed in another PR)
* fixed more compile warnings and the remaining test failures (hopefully)
* trying to fix the last little warning
This is a fix to the signature of static function
collectCalibrationData() and clean-up for #12772. Since fallback scheme
in calibration method selection is not used anymore. As an input
parameter, iFixedPoint should be passed by value according to the OpenCV
coding style guide.
More accurate pinhole camera calibration with imperfect planar target (#12772)
43 commits:
* Add derivatives with respect to object points
Add an output parameter to calculate derivatives of image points with
respect to 3D coordinates of object points. The output jacobian matrix
is a 2Nx3N matrix where N is the number of points.
This commit introduces incompatibility to old function signature.
* Set zero for dpdo matrix before using
dpdo is a sparse matrix with only non-zero value close to major
diagonal. Set it to zero because only elements near major diagonal are
computed.
* Add jacobian columns to projectPoints()
The output jacobian matrix of derivatives with respect to coordinates of
3D object points are added. This might break callers who assume the
columns of jacobian matrix.
* Adapt test code to updated project functions
The test cases for projectPoints() and cvProjectPoints2() are updated to
fit new function signatures.
* Add accuracy test code for dpdo
* Add badarg test for dpdo
* Add new enum item for new calibration method
CALIB_RELEASE_OBJECT is used to whether to release 3D coordinates of
object points. The method was proposed in: K. H. Strobl and G. Hirzinger.
"More Accurate Pinhole Camera Calibration with Imperfect Planar Target".
In Proceedings of the IEEE International Conference on Computer Vision
(ICCV 2011), 1st IEEE Workshop on Challenges and Opportunities in Robot
Perception, Barcelona, Spain, pp. 1068-1075, November 2011.
* Add releasing object method into internal function
It's a simple extension of the standard calibration scheme. We choose to
fix the first and last object point and a user-selected fixed point.
* Add interfaces for extended calibration method
* Refine document for calibrateCamera()
When releasing object points, only the z coordinates of the
objectPoints[0].back is fixed.
* Add link to strobl2011iccv paper
* Improve documentation for calibrateCamera()
* Add implementations of wrapping calibrateCamera()
* Add checking for params of new calibration method
If input parameters are not qualified, then fall back to standard
calibration method.
* Add camera calibration method of releasing object
The current implementation is equal to or better than
https://github.com/xoox/calibrel
* Update doc for CALIB_RELEASE_OBJECT
CALIB_USE_QR or CALIB_USE_LU could be used for faster calibration with
potentially less precise and less stable in some rare cases.
* Add RELEASE_OBJECT calibration to tutorial code
To select the calibration method of releasing object points, a command
line parameter `-d=<number>` should be provided.
* Update tutorial doc for camera_calibration
If the method of releasing object points is merged into OpenCV. It will
be expected to be firstly released in 4.1, I think.
* Reduce epsilon for cornerSubPix()
Epsilon of 0.1 is a bigger one. Preciser corner positions are required
with calibration method of releasing object.
* Refine camera calibration tutorial
The hypothesis coordinates are used to indicate which distance must be
measured between two specified object points.
* Update sample calibration code method selection
Similar to camera_calibration tutorial application, a command line
argument `-dt=<number>` is used to select the calibration method.
* Add guard to flags of cvCalibrateCamera2()
cvCalibrateCamera2() doesn't accept CALIB_RELEASE_OBJECT unless overload
interface is added in the future.
* Simplify fallback when iFixedPoint is out of range
* Refactor projectPoints() to keep compatibilities
* Fix arg string "Bad rvecs header"
* Read calibration flags from test data files
Instead of being hard coded into source file, the calibration flags will
be read from test data files.
opencv_extra/testdata/cv/cameracalibration/calib?.dat must be sync with
the test code.
* Add new C interface of cvCalibrateCamera4()
With this new added C interface, the extended calibration method with
CALIB_RELEASE_OBJECT can be called by C API.
* Add regression test of extended calibration method
It has been tested with new added test data in xoox:calib-release-object
branch of opencv_extra.
* Fix assertion in test_cameracalibration.cpp
The total number of refined 3D object coordinates is checked.
* Add checker for iFixedPoint in cvCalibrateCamera4
If iFixedPoint is out of rational range, fall back to standard method.
* Fix documentation for overloaded calibrateCamera()
* Remove calibration flag of CALIB_RELEASE_OBJECT
The method selection is based on the range of the index of fixed point.
For minus values, standard calibration method will be chosen. Values in
a rational range will make the object-releasing calibration method
selected.
* Use new interfaces instead of function overload
Existing interfaces are preserved and new interfaces are added. Since
most part of the code base are shared, calibrateCamera() is now a
wrapper function of calibrateCameraRO().
* Fix exported name of calibrateCameraRO()
* Update documentation for calibrateCameraRO()
The circumstances where this method is mostly helpful are described.
* Add note on the rigidity of the calibration target
* Update documentation for calibrateCameraRO()
It is clarified that iFixedPoint is used as a switch to select
calibration method. If input data are not qualified, exceptions will be
thrown instead of fallback scheme.
* Clarify iFixedPoint as switch and remove fallback
iFixedPoint is now used as a switch for calibration method selection. No
fallback scheme is utilized anymore. If the input data are not
qualified, exceptions will be thrown.
* Add badarg test for object-releasing method
* Fix document format of sample list
List items of same level should be indented the same way. Otherwise they
will be formatted as nested lists by Doxygen.
* Add brief intro for objectPoints and imagePoints
* Sync tutorial to sample calibration code
* Update tutorial compatibility version to 4.0
- avoid updating of input image during equalizeHist() call
- avoid for() with double variable (use 'int' instead)
- more CV_Check*() macros
- use Mat_<T>, Matx
- static for local variables
findChessboardCornersSB: speed improvements (#12615)
* chessboard: fix do not modify const image
* chessboard: speed up scale space using parallel_for
* chessboard: small improvements
* chessboard: speed up board growing using parallel_for
* chessboard: add flags for tuning detection
* chessboard: fix compiler warnings
* chessborad: change flag name to CALIB_CB_EXHAUSTIVE
This also fixes a typo
* chessboard: fix const ref + remove to_string
Before this fix, the code would fail if only standard deviations of
extrinsic parameters are requested. While standard deviations matrix
should be computed if any set of standard deviations is requested. A
variable is added to represent this case.
* add new chessboard detector
The chessboar detector is based on the paper.
Accurate Detection and Localization of Checkerboard Corners for
Calibration Alexander Duda, Udo Frese
British Machine Vision Conference, o.A., 2018.
It utilizes point symmetry of checkerboard corners in combination with a
localized Radon transform approximated by box filters to achieve high
performance even on large images. Here, tests have shown that the
ability to localize checkerboard corners is close to the theoretical
limit of 1/100 of a pixel while being considerably less sensitive
to image noise than standard methods.
* chessboard: add reference to bibtex file
* chessboard: add dependency to opencv_flann
* fix: test chesscorners. It is valid to return an empty list
In case no chessboard was detected it should be valid for the detector
to return an empty list.
For simplifcation, it should be allowed to return any number of corners
if they are flagged as not found.
* fix: opencv.bib remove empty lines
* fix: doc findChessboardCorners replace cvSize with cv::Size
* chessboard tests: factor out logic selecting detector
* chessboard: add unit test for findChessboardCorners2
This is includes a new chessboard generator which supports subpix
corners with high accuracy by wrapping an optimal chessboard using
wrapPerspective.
* fix: chessboard unit test - overwrite of default parameter flag of findCirclesGrid
* chessboard: remove trailing whitespace
* chessboard: fix debug drawing
* chessboard: fix some issues during code review
* chessboard: normalize asymmetric chessboard
* chessboard: fix float double warning
* remove trailing whitespace
* chessboards: fix compiler warnings
* chessboards: fix compiler warnings
* checkerboard: some performance improvements
* chessboard: remove NULL macros for language bindinges from internal headers
* chessboard: shorten license terms
* chessboard: remove unused internal method
* chessboard: set helper functions to static
* chessboard: fix normalizePoints1D using unshifted points
* chessboard: remove wrongly copied text
* chessboard: use CV_CheckTypeEQ macro
* chessboard: comment all NaN checks
* chessboard: use consistent color conversion
* chessboard: use CheckChannelEQ macro
* chessboard: assume gray color image for internal methods
* chessboard: use std::swap
* chessboard: use Mat.dataend
* chessboard: fix compiler warnings
* chessboard: replace some checks witch CV_CHECK macro
* chessboard: fix comparison function for partial sort
* chessboard: small cleanup
* chessboard: use short license header
* chessboard: rename findChessboard2 to findChessboardSB
* chessboard: fix type in unit test
* trying to fix the custom AVX2 builder test failures (false alarms)
* fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests
* fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests
* fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests
* seemingly disabled false alarm warning in surf.cpp; increased tolerance thresholds in the tests for SolvePnP and in DNN/ENet
* Add HPX backend for OpenCV implementation
Adds hpx backend for cv::parallel_for_() calls respecting the nstripes chunking parameter. C++ code for the backend is added to modules/core/parallel.cpp. Also, the necessary changes to cmake files are introduced.
Backend can operate in 2 versions (selectable by cmake build option WITH_HPX_STARTSTOP): hpx (runtime always on) and hpx_startstop (start and stop the backend for each cv::parallel_for_() call)
* WIP: Conditionally include hpx_main.hpp to tests in core module
Header hpx_main.hpp is included to both core/perf/perf_main.cpp and core/test/test_main.cpp.
The changes to cmake files for linking hpx library to above mentioned test executalbles are proposed but have issues.
* Add coditional iclusion of hpx_main.hpp to cpp cpu modules
* Remove start/stop version of hpx backend
