OpenCV 4.12.0
开源计算机视觉
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类 | 命名空间 | 类型定义 | 枚举 | 函数
calib3d.hpp 文件参考
#include "opencv2/core.hpp"
#include "opencv2/core/types.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/core/affine.hpp"
#include "opencv2/core/utils/logger.hpp"
calib3d.hpp 的包含依赖关系图
此图显示了哪些文件直接或间接包含此文件

类

类  cv::LMSolver::Callback
 
结构体  cv::CirclesGridFinderParameters
 
类  cv::LMSolver
 
类  cv::StereoBM
 用于使用块匹配算法计算立体对应关系的类，由 K. Konolige 引入并贡献给 OpenCV。更多...
 
类  cv::StereoMatcher
 立体对应算法的基类。更多...
 
类  cv::StereoSGBM
 该类实现了修改后的 H. Hirschmuller 算法 [128]，与原始算法的不同之处如下：更多...
 
结构体  cv::UsacParams
 

命名空间

命名空间  cv
 
命名空间  cv::fisheye
 此命名空间中的方法使用所谓的鱼眼相机模型。
 

类型定义

typedef CirclesGridFinderParameters cv::CirclesGridFinderParameters2
 

枚举

枚举  {
  cv::fisheye::CALIB_USE_INTRINSIC_GUESS = 1 << 0 ,
  cv::fisheye::CALIB_RECOMPUTE_EXTRINSIC = 1 << 1 ,
  cv::fisheye::CALIB_CHECK_COND = 1 << 2 ,
  cv::fisheye::CALIB_FIX_SKEW = 1 << 3 ,
  cv::fisheye::CALIB_FIX_K1 = 1 << 4 ,
  cv::fisheye::CALIB_FIX_K2 = 1 << 5 ,
  cv::fisheye::CALIB_FIX_K3 = 1 << 6 ,
  cv::fisheye::CALIB_FIX_K4 = 1 << 7 ,
  cv::fisheye::CALIB_FIX_INTRINSIC = 1 << 8 ,
  cv::fisheye::CALIB_FIX_PRINCIPAL_POINT = 1 << 9 ,
  cv::fisheye::CALIB_ZERO_DISPARITY = 1 << 10 ,
  cv::fisheye::CALIB_FIX_FOCAL_LENGTH = 1 << 11
}
 
枚举  {
  cv::LMEDS = 4 ,
  cv::RANSAC = 8 ,
  cv::RHO = 16 ,
  cv::USAC_DEFAULT = 32 ,
  cv::USAC_PARALLEL = 33 ,
  cv::USAC_FM_8PTS = 34 ,
  cv::USAC_FAST = 35 ,
  cv::USAC_ACCURATE = 36 ,
  cv::USAC_PROSAC = 37 ,
  cv::USAC_MAGSAC = 38
}
 鲁棒估计算法类型 更多...
 
枚举  {
  cv::CALIB_CB_ADAPTIVE_THRESH = 1 ,
  cv::CALIB_CB_NORMALIZE_IMAGE = 2 ,
  cv::CALIB_CB_FILTER_QUADS = 4 ,
  cv::CALIB_CB_FAST_CHECK = 8 ,
  cv::CALIB_CB_EXHAUSTIVE = 16 ,
  cv::CALIB_CB_ACCURACY = 32 ,
  cv::CALIB_CB_LARGER = 64 ,
  cv::CALIB_CB_MARKER = 128 ,
  cv::CALIB_CB_PLAIN = 256
}
 
枚举  {
  cv::CALIB_CB_SYMMETRIC_GRID = 1 ,
  cv::CALIB_CB_ASYMMETRIC_GRID = 2 ,
  cv::CALIB_CB_CLUSTERING = 4
}
 
枚举  {
  cv::CALIB_NINTRINSIC = 18 ,
  cv::CALIB_USE_INTRINSIC_GUESS = 0x00001 ,
  cv::CALIB_FIX_ASPECT_RATIO = 0x00002 ,
  cv::CALIB_FIX_PRINCIPAL_POINT = 0x00004 ,
  cv::CALIB_ZERO_TANGENT_DIST = 0x00008 ,
  cv::CALIB_FIX_FOCAL_LENGTH = 0x00010 ,
  cv::CALIB_FIX_K1 = 0x00020 ,
  cv::CALIB_FIX_K2 = 0x00040 ,
  cv::CALIB_FIX_K3 = 0x00080 ,
  cv::CALIB_FIX_K4 = 0x00800 ,
  cv::CALIB_FIX_K5 = 0x01000 ,
  cv::CALIB_FIX_K6 = 0x02000 ,
  cv::CALIB_RATIONAL_MODEL = 0x04000 ,
  cv::CALIB_THIN_PRISM_MODEL = 0x08000 ,
  cv::CALIB_FIX_S1_S2_S3_S4 = 0x10000 ,
  cv::CALIB_TILTED_MODEL = 0x40000 ,
  cv::CALIB_FIX_TAUX_TAUY = 0x80000 ,
  cv::CALIB_USE_QR = 0x100000 ,
  cv::CALIB_FIX_TANGENT_DIST = 0x200000 ,
  cv::CALIB_FIX_INTRINSIC = 0x00100 ,
  cv::CALIB_SAME_FOCAL_LENGTH = 0x00200 ,
  cv::CALIB_ZERO_DISPARITY = 0x00400 ,
  cv::CALIB_USE_LU = (1 << 17) ,
  cv::CALIB_USE_EXTRINSIC_GUESS = (1 << 22)
}
 
枚举  {
  cv::FM_7POINT = 1 ,
  cv::FM_8POINT = 2 ,
  cv::FM_LMEDS = 4 ,
  cv::FM_RANSAC = 8
}
 查找基本矩阵的算法 更多...
 
枚举  cv::HandEyeCalibrationMethod {
  cv::CALIB_HAND_EYE_TSAI = 0 ,
  cv::CALIB_HAND_EYE_PARK = 1 ,
  cv::CALIB_HAND_EYE_HORAUD = 2 ,
  cv::CALIB_HAND_EYE_ANDREFF = 3 ,
  cv::CALIB_HAND_EYE_DANIILIDIS = 4
}
 
枚举  cv::LocalOptimMethod {
  cv::LOCAL_OPTIM_NULL =0 ,
  cv::LOCAL_OPTIM_INNER_LO =1 ,
  cv::LOCAL_OPTIM_INNER_AND_ITER_LO =2 ,
  cv::LOCAL_OPTIM_GC =3 ,
  cv::LOCAL_OPTIM_SIGMA =4
}
 
枚举  cv::NeighborSearchMethod {
  cv::NEIGH_FLANN_KNN =0 ,
  cv::NEIGH_GRID =1 ,
  cv::NEIGH_FLANN_RADIUS =2
}
 
枚举  cv::PolishingMethod {
  cv::NONE_POLISHER =0 ,
  cv::LSQ_POLISHER =1 ,
  cv::MAGSAC =2 ,
  cv::COV_POLISHER =3
}
 
枚举  cv::RobotWorldHandEyeCalibrationMethod {
  cv::CALIB_ROBOT_WORLD_HAND_EYE_SHAH = 0 ,
  cv::CALIB_ROBOT_WORLD_HAND_EYE_LI = 1
}
 
枚举  cv::SamplingMethod {
  cv::SAMPLING_UNIFORM =0 ,
  cv::SAMPLING_PROGRESSIVE_NAPSAC =1 ,
  cv::SAMPLING_NAPSAC =2 ,
  cv::SAMPLING_PROSAC =3
}
 
枚举  cv::ScoreMethod {
  cv::SCORE_METHOD_RANSAC =0 ,
  cv::SCORE_METHOD_MSAC =1 ,
  cv::SCORE_METHOD_MAGSAC =2 ,
  cv::SCORE_METHOD_LMEDS =3
}
 
枚举  cv::SolvePnPMethod {
  cv::SOLVEPNP_ITERATIVE = 0 ,
  cv::SOLVEPNP_EPNP = 1 ,
  cv::SOLVEPNP_P3P = 2 ,
  cv::SOLVEPNP_DLS = 3 ,
  cv::SOLVEPNP_UPNP = 4 ,
  cv::SOLVEPNP_AP3P = 5 ,
  cv::SOLVEPNP_IPPE = 6 ,
  cv::SOLVEPNP_IPPE_SQUARE = 7 ,
  cv::SOLVEPNP_SQPNP = 8
}
 
枚举  cv::UndistortTypes {
  cv::PROJ_SPHERICAL_ORTHO = 0 ,
  cv::PROJ_SPHERICAL_EQRECT = 1
}
 cv::undistort 模式 更多...
 

函数

double cv::fisheye::calibrate (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, const Size &image_size, InputOutputArray K, InputOutputArray D, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags=0, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 100, DBL_EPSILON))
 执行相机标定。
 
double cv::calibrateCamera (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags=0, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON))
 
double cv::calibrateCamera (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, OutputArray stdDeviationsIntrinsics, OutputArray stdDeviationsExtrinsics, OutputArray perViewErrors, int flags=0, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON))
 从标定模式的多个视图中查找相机内参和外参。
 
double cv::calibrateCameraRO (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, Size imageSize, int iFixedPoint, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, OutputArray newObjPoints, int flags=0, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON))
 
double cv::calibrateCameraRO (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, Size imageSize, int iFixedPoint, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, OutputArray newObjPoints, OutputArray stdDeviationsIntrinsics, OutputArray stdDeviationsExtrinsics, OutputArray stdDeviationsObjPoints, OutputArray perViewErrors, int flags=0, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON))
 从标定模式的多个视图中查找相机内参和外参。
 
void cv::calibrateHandEye (InputArrayOfArrays R_gripper2base, InputArrayOfArrays t_gripper2base, InputArrayOfArrays R_target2cam, InputArrayOfArrays t_target2cam, OutputArray R_cam2gripper, OutputArray t_cam2gripper, HandEyeCalibrationMethod method=CALIB_HAND_EYE_TSAI)
 计算手眼标定：\(_{}^{g}\textrm{T}_c\)。
 
void cv::calibrateRobotWorldHandEye (InputArrayOfArrays R_world2cam, InputArrayOfArrays t_world2cam, InputArrayOfArrays R_base2gripper, InputArrayOfArrays t_base2gripper, OutputArray R_base2world, OutputArray t_base2world, OutputArray R_gripper2cam, OutputArray t_gripper2cam, RobotWorldHandEyeCalibrationMethod method=CALIB_ROBOT_WORLD_HAND_EYE_SHAH)
 计算机器人-世界/手眼标定：\(_{}^{w}\textrm{T}_b\) 和 \(_{}^{c}\textrm{T}_g\)。
 
void cv::calibrationMatrixValues (InputArray cameraMatrix, Size imageSize, double apertureWidth, double apertureHeight, double &fovx, double &fovy, double &focalLength, Point2d &principalPoint, double &aspectRatio)
 从相机内参矩阵计算有用的相机特性。
 
bool cv::checkChessboard (InputArray img, Size size)
 
void cv::composeRT (InputArray rvec1, InputArray tvec1, InputArray rvec2, InputArray tvec2, OutputArray rvec3, OutputArray tvec3, OutputArray dr3dr1=noArray(), OutputArray dr3dt1=noArray(), OutputArray dr3dr2=noArray(), OutputArray dr3dt2=noArray(), OutputArray dt3dr1=noArray(), OutputArray dt3dt1=noArray(), OutputArray dt3dr2=noArray(), OutputArray dt3dt2=noArray())
 组合两个旋转平移变换。
 
void cv::computeCorrespondEpilines (InputArray points, int whichImage, InputArray F, OutputArray lines)
 对于立体图像对中一个图像中的点，计算另一个图像中的对应极线。
 
void cv::convertPointsFromHomogeneous (InputArray src, OutputArray dst)
 将点从齐次坐标空间转换为欧几里得空间。
 
void cv::convertPointsHomogeneous (InputArray src, OutputArray dst)
 将点转换为齐次坐标或从齐次坐标转换。
 
void cv::convertPointsToHomogeneous (InputArray src, OutputArray dst)
 将点从欧几里得空间转换为齐次空间。
 
void cv::correctMatches (InputArray F, InputArray points1, InputArray points2, OutputArray newPoints1, OutputArray newPoints2)
 细化对应点的坐标。
 
void cv::decomposeEssentialMat (InputArray E, OutputArray R1, OutputArray R2, OutputArray t)
 将本征矩阵分解为可能的旋转和平移。
 
int cv::decomposeHomographyMat (InputArray H, InputArray K, OutputArrayOfArrays rotations, OutputArrayOfArrays translations, OutputArrayOfArrays normals)
 将单应性矩阵分解为旋转、平移和平面法线。
 
void cv::decomposeProjectionMatrix (InputArray projMatrix, OutputArray cameraMatrix, OutputArray rotMatrix, OutputArray transVect, OutputArray rotMatrixX=noArray(), OutputArray rotMatrixY=noArray(), OutputArray rotMatrixZ=noArray(), OutputArray eulerAngles=noArray())
 将投影矩阵分解为旋转矩阵和相机内参矩阵。
 
void cv::fisheye::distortPoints (InputArray undistorted, OutputArray distorted, InputArray K, InputArray D, double alpha=0)
 使用鱼眼模型扭曲 2D 点。
 
void cv::fisheye::distortPoints (InputArray undistorted, OutputArray distorted, InputArray Kundistorted, InputArray K, InputArray D, double alpha=0)
 
void cv::drawChessboardCorners (InputOutputArray image, Size patternSize, InputArray corners, bool patternWasFound)
 渲染检测到的棋盘角点。
 
void cv::drawFrameAxes (InputOutputArray image, InputArray cameraMatrix, InputArray distCoeffs, InputArray rvec, InputArray tvec, float length, int thickness=3)
 从姿态估计中绘制世界/对象坐标系的轴。
 
cv::Mat cv::estimateAffine2D (InputArray from, InputArray to, OutputArray inliers=noArray(), int method=RANSAC, double ransacReprojThreshold=3, size_t maxIters=2000, double confidence=0.99, size_t refineIters=10)
 计算两个二维点集之间的最优仿射变换。
 
cv::Mat cv::estimateAffine2D (InputArray pts1, InputArray pts2, OutputArray inliers, const UsacParams &params)
 
cv::Mat cv::estimateAffine3D (InputArray src, InputArray dst, double *scale=nullptr, bool force_rotation=true)
 计算两个三维点集之间的最优仿射变换。
 
int cv::estimateAffine3D (InputArray src, InputArray dst, OutputArray out, OutputArray inliers, double ransacThreshold=3, double confidence=0.99)
 计算两个三维点集之间的最优仿射变换。
 
cv::Mat cv::estimateAffinePartial2D (InputArray from, InputArray to, OutputArray inliers=noArray(), int method=RANSAC, double ransacReprojThreshold=3, size_t maxIters=2000, double confidence=0.99, size_t refineIters=10)
 计算两个二维点集之间具有4个自由度的最优受限仿射变换。
 
Scalar cv::estimateChessboardSharpness (InputArray image, Size patternSize, InputArray corners, float rise_distance=0.8F, bool vertical=false, OutputArray sharpness=noArray())
 估计检测到的棋盘的清晰度。
 
void cv::fisheye::estimateNewCameraMatrixForUndistortRectify (InputArray K, InputArray D, const Size &image_size, InputArray R, OutputArray P, double balance=0.0, const Size &new_size=Size(), double fov_scale=1.0)
 估算用于去畸变或校正的新相机内参矩阵。
 
int cv::estimateTranslation3D (InputArray src, InputArray dst, OutputArray out, OutputArray inliers, double ransacThreshold=3, double confidence=0.99)
 计算两个三维点集之间的最优平移。
 
void cv::filterHomographyDecompByVisibleRefpoints (InputArrayOfArrays rotations, InputArrayOfArrays normals, InputArray beforePoints, InputArray afterPoints, OutputArray possibleSolutions, InputArray pointsMask=noArray())
 根据附加信息过滤单应性分解。
 
void cv::filterSpeckles (InputOutputArray img, double newVal, int maxSpeckleSize, double maxDiff, InputOutputArray buf=noArray())
 过滤视差图中小的噪声斑点。
 
bool cv::find4QuadCornerSubpix (InputArray img, InputOutputArray corners, Size region_size)
 查找棋盘角点的亚像素精确位置
 
bool cv::findChessboardCorners (InputArray image, Size patternSize, OutputArray corners, int flags=CALIB_CB_ADAPTIVE_THRESH+CALIB_CB_NORMALIZE_IMAGE)
 查找棋盘内部角点的位置。
 
bool cv::findChessboardCornersSB (InputArray image, Size patternSize, OutputArray corners, int flags, OutputArray meta)
 使用基于扇区的方法查找棋盘内部角点的位置。
 
bool cv::findChessboardCornersSB (InputArray image, Size patternSize, OutputArray corners, int flags=0)
 
bool cv::findCirclesGrid (InputArray image, Size patternSize, OutputArray centers, int flags, const Ptr< FeatureDetector > &blobDetector, const CirclesGridFinderParameters &parameters)
 在圆形网格中查找中心。
 
bool cv::findCirclesGrid (InputArray image, Size patternSize, OutputArray centers, int flags=CALIB_CB_SYMMETRIC_GRID, const Ptr< FeatureDetector > &blobDetector=SimpleBlobDetector::create())
 
Mat cv::findEssentialMat (InputArray points1, InputArray points2, double focal, Point2d pp, int method, double prob, double threshold, OutputArray mask)
 
Mat cv::findEssentialMat (InputArray points1, InputArray points2, double focal=1.0, Point2d pp=Point2d(0, 0), int method=RANSAC, double prob=0.999, double threshold=1.0, int maxIters=1000, OutputArray mask=noArray())
 
Mat cv::findEssentialMat (InputArray points1, InputArray points2, InputArray cameraMatrix, int method, double prob, double threshold, OutputArray mask)
 
Mat cv::findEssentialMat (InputArray points1, InputArray points2, InputArray cameraMatrix, int method=RANSAC, double prob=0.999, double threshold=1.0, int maxIters=1000, OutputArray mask=noArray())
 从两幅图像中的对应点计算本征矩阵。
 
Mat cv::findEssentialMat (InputArray points1, InputArray points2, InputArray cameraMatrix1, InputArray cameraMatrix2, InputArray dist_coeff1, InputArray dist_coeff2, OutputArray mask, const UsacParams &params)
 
Mat cv::findEssentialMat (InputArray points1, InputArray points2, InputArray cameraMatrix1, InputArray distCoeffs1, InputArray cameraMatrix2, InputArray distCoeffs2, int method=RANSAC, double prob=0.999, double threshold=1.0, OutputArray mask=noArray())
 从可能来自两个不同相机的两幅图像中的对应点计算本征矩阵。
 
Mat cv::findFundamentalMat (InputArray points1, InputArray points2, int method, double ransacReprojThreshold, double confidence, int maxIters, OutputArray mask=noArray())
 从两幅图像中的对应点计算基本矩阵。
 
Mat cv::findFundamentalMat (InputArray points1, InputArray points2, int method=FM_RANSAC, double ransacReprojThreshold=3., double confidence=0.99, OutputArray mask=noArray())
 
Mat cv::findFundamentalMat (InputArray points1, InputArray points2, OutputArray mask, const UsacParams &params)
 
Mat cv::findFundamentalMat (InputArray points1, InputArray points2, OutputArray mask, int method=FM_RANSAC, double ransacReprojThreshold=3., double confidence=0.99)
 
Mat cv::findHomography (InputArray srcPoints, InputArray dstPoints, int method=0, double ransacReprojThreshold=3, OutputArray mask=noArray(), const int maxIters=2000, const double confidence=0.995)
 在两个平面之间找到透视变换。
 
Mat cv::findHomography (InputArray srcPoints, InputArray dstPoints, OutputArray mask, const UsacParams &params)
 
Mat cv::findHomography (InputArray srcPoints, InputArray dstPoints, OutputArray mask, int method=0, double ransacReprojThreshold=3)
 
Mat cv::getDefaultNewCameraMatrix (InputArray cameraMatrix, Size imgsize=Size(), bool centerPrincipalPoint=false)
 返回默认的新相机矩阵。
 
Mat cv::getOptimalNewCameraMatrix (InputArray cameraMatrix, InputArray distCoeffs, Size imageSize, double alpha, Size newImgSize=Size(), Rect *validPixROI=0, bool centerPrincipalPoint=false)
 根据自由缩放参数返回新的相机内参矩阵。
 
Rect cv::getValidDisparityROI (Rect roi1, Rect roi2, int minDisparity, int numberOfDisparities, int blockSize)
 从校正图像的有效 ROI（由 stereoRectify 返回）计算有效视差 ROI
 
Mat cv::initCameraMatrix2D (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, Size imageSize, double aspectRatio=1.0)
 从 3D-2D 点对应关系中查找初始相机内参矩阵。
 
void cv::initInverseRectificationMap (InputArray cameraMatrix, InputArray distCoeffs, InputArray R, InputArray newCameraMatrix, const Size &size, int m1type, OutputArray map1, OutputArray map2)
 计算投影和逆校正变换图。本质上，这是 initUndistortRectifyMap 的逆操作，用于适应投影仪（“逆相机”）在投影仪-相机对中的立体校正。
 
void cv::fisheye::initUndistortRectifyMap (InputArray K, InputArray D, InputArray R, InputArray P, const cv::Size &size, int m1type, OutputArray map1, OutputArray map2)
 计算用于通过 remap 进行图像变换的去畸变和校正图。如果 D 为空，则使用零畸变；如果 R 或 P 为空，则使用单位矩阵。
 
void cv::initUndistortRectifyMap (InputArray cameraMatrix, InputArray distCoeffs, InputArray R, InputArray newCameraMatrix, Size size, int m1type, OutputArray map1, OutputArray map2)
 计算去畸变和校正变换图。
 
float cv::initWideAngleProjMap (InputArray cameraMatrix, InputArray distCoeffs, Size imageSize, int destImageWidth, int m1type, OutputArray map1, OutputArray map2, enum UndistortTypes projType=PROJ_SPHERICAL_EQRECT, double alpha=0)
 初始化广角 remap 的映射
 
static float cv::initWideAngleProjMap (InputArray cameraMatrix, InputArray distCoeffs, Size imageSize, int destImageWidth, int m1type, OutputArray map1, OutputArray map2, int projType, double alpha=0)
 
void cv::matMulDeriv (InputArray A, InputArray B, OutputArray dABdA, OutputArray dABdB)
 计算每个相乘矩阵的矩阵乘积的偏导数。
 
void cv::fisheye::projectPoints (InputArray objectPoints, OutputArray imagePoints, const Affine3d &affine, InputArray K, InputArray D, double alpha=0, OutputArray jacobian=noArray())
 使用鱼眼模型投影点。
 
void cv::fisheye::projectPoints (InputArray objectPoints, OutputArray imagePoints, InputArray rvec, InputArray tvec, InputArray K, InputArray D, double alpha=0, OutputArray jacobian=noArray())
 
void cv::projectPoints (InputArray objectPoints, InputArray rvec, InputArray tvec, InputArray cameraMatrix, InputArray distCoeffs, OutputArray imagePoints, OutputArray jacobian=noArray(), double aspectRatio=0)
 将三维点投影到图像平面。
 
int cv::recoverPose (InputArray E, InputArray points1, InputArray points2, InputArray cameraMatrix, OutputArray R, OutputArray t, double distanceThresh, InputOutputArray mask=noArray(), OutputArray triangulatedPoints=noArray())
 
int cv::recoverPose (InputArray E, InputArray points1, InputArray points2, InputArray cameraMatrix, OutputArray R, OutputArray t, InputOutputArray mask=noArray())
 从估计的本征矩阵和两幅图像中的对应点中恢复相对相机旋转和平移，并使用手性检查。返回通过检查的内点数量。
 
int cv::recoverPose (InputArray E, InputArray points1, InputArray points2, OutputArray R, OutputArray t, double focal=1.0, Point2d pp=Point2d(0, 0), InputOutputArray mask=noArray())
 
int cv::recoverPose (InputArray points1, InputArray points2, InputArray cameraMatrix1, InputArray distCoeffs1, InputArray cameraMatrix2, InputArray distCoeffs2, OutputArray E, OutputArray R, OutputArray t, int method=cv::RANSAC, double prob=0.999, double threshold=1.0, InputOutputArray mask=noArray())
 从来自两个不同相机的两幅图像中的对应点中恢复相对相机旋转和平移，并使用手性检查。返回通过检查的内点数量。
 
float cv::rectify3Collinear (InputArray cameraMatrix1, InputArray distCoeffs1, InputArray cameraMatrix2, InputArray distCoeffs2, InputArray cameraMatrix3, InputArray distCoeffs3, InputArrayOfArrays imgpt1, InputArrayOfArrays imgpt3, Size imageSize, InputArray R12, InputArray T12, InputArray R13, InputArray T13, OutputArray R1, OutputArray R2, OutputArray R3, OutputArray P1, OutputArray P2, OutputArray P3, OutputArray Q, double alpha, Size newImgSize, Rect *roi1, Rect *roi2, int flags)
 计算三头相机的校正变换，其中所有相机头都在同一直线上。
 
void cv::reprojectImageTo3D (InputArray disparity, OutputArray _3dImage, InputArray Q, bool handleMissingValues=false, int ddepth=-1)
 将视差图像重新投影到3D空间。
 
void cv::Rodrigues (InputArray src, OutputArray dst, OutputArray jacobian=noArray())
 将旋转矩阵转换为旋转向量，反之亦然。
 
Vec3d cv::RQDecomp3x3 (InputArray src, OutputArray mtxR, OutputArray mtxQ, OutputArray Qx=noArray(), OutputArray Qy=noArray(), OutputArray Qz=noArray())
 计算3x3矩阵的RQ分解。
 
double cv::sampsonDistance (InputArray pt1, InputArray pt2, InputArray F)
 计算两点之间的Sampson距离。
 
int cv::solveP3P (InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags)
 从3个3D-2D点对应关系中查找对象姿态 \( {}^{c}\mathbf{T}_o \)。
 
bool cv::fisheye::solvePnP (InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess=false, int flags=SOLVEPNP_ITERATIVE, TermCriteria criteria=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 10, 1e-8))
 使用鱼眼相机模型从 3D-2D 点对应关系中查找对象姿态。
 
bool cv::solvePnP (InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess=false, int flags=SOLVEPNP_ITERATIVE)
 从 3D-2D 点对应关系中查找对象姿态 \( {}^{c}\mathbf{T}_o \)
 
int cv::solvePnPGeneric (InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, bool useExtrinsicGuess=false, SolvePnPMethod flags=SOLVEPNP_ITERATIVE, InputArray rvec=noArray(), InputArray tvec=noArray(), OutputArray reprojectionError=noArray())
 从 3D-2D 点对应关系中查找对象姿态 \( {}^{c}\mathbf{T}_o \)。
 
bool cv::fisheye::solvePnPRansac (InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess=false, int iterationsCount=100, float reprojectionError=8.0, double confidence=0.99, OutputArray inliers=noArray(), int flags=SOLVEPNP_ITERATIVE, TermCriteria criteria=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 10, 1e-8))
 使用 RANSAC 方案从 3D-2D 点对应关系中查找鱼眼相机模型下的对象姿态。
 
bool cv::solvePnPRansac (InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess=false, int iterationsCount=100, float reprojectionError=8.0, double confidence=0.99, OutputArray inliers=noArray(), int flags=SOLVEPNP_ITERATIVE)
 使用 RANSAC 方案从 3D-2D 点对应关系中查找对象姿态 \( {}^{c}\mathbf{T}_o \)，以处理不匹配的情况。
 
bool cv::solvePnPRansac (InputArray objectPoints, InputArray imagePoints, InputOutputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, OutputArray tvec, OutputArray inliers, const UsacParams &params=UsacParams())
 
void cv::solvePnPRefineLM (InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, InputOutputArray rvec, InputOutputArray tvec, TermCriteria criteria=TermCriteria(TermCriteria::EPS+TermCriteria::COUNT, 20, FLT_EPSILON))
 从 3D-2D 点对应关系和初始解开始，优化姿态（将以对象坐标系表示的 3D 点转换为相机坐标系的平移和旋转）。
 
void cv::solvePnPRefineVVS (InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, InputOutputArray rvec, InputOutputArray tvec, TermCriteria criteria=TermCriteria(TermCriteria::EPS+TermCriteria::COUNT, 20, FLT_EPSILON), double VVSlambda=1)
 从 3D-2D 点对应关系和初始解开始，优化姿态（将以对象坐标系表示的 3D 点转换为相机坐标系的平移和旋转）。
 
double cv::fisheye::stereoCalibrate (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, InputOutputArray K1, InputOutputArray D1, InputOutputArray K2, InputOutputArray D2, Size imageSize, OutputArray R, OutputArray T, int flags=fisheye::CALIB_FIX_INTRINSIC, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 100, DBL_EPSILON))
 这是一个重载成员函数，为方便起见提供。它与上述函数的唯一区别在于它接受的参数。
 
double cv::fisheye::stereoCalibrate (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, InputOutputArray K1, InputOutputArray D1, InputOutputArray K2, InputOutputArray D2, Size imageSize, OutputArray R, OutputArray T, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags=fisheye::CALIB_FIX_INTRINSIC, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 100, DBL_EPSILON))
 执行立体标定。
 
double cv::stereoCalibrate (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1, InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2, Size imageSize, InputOutputArray R, InputOutputArray T, OutputArray E, OutputArray F, OutputArray perViewErrors, int flags=CALIB_FIX_INTRINSIC, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6))
 这是一个重载成员函数，为方便起见提供。它与上述函数的唯一区别在于它接受的参数。
 
double cv::stereoCalibrate (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1, InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2, Size imageSize, InputOutputArray R, InputOutputArray T, OutputArray E, OutputArray F, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, OutputArray perViewErrors, int flags=CALIB_FIX_INTRINSIC, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6))
 标定立体相机设置。此函数查找两个相机各自的内参以及两个相机之间的外参。
 
double cv::stereoCalibrate (InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1, InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2, Size imageSize, OutputArray R, OutputArray T, OutputArray E, OutputArray F, int flags=CALIB_FIX_INTRINSIC, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6))
 这是一个重载成员函数，为方便起见提供。它与上述函数的唯一区别在于它接受的参数。
 
void cv::fisheye::stereoRectify (InputArray K1, InputArray D1, InputArray K2, InputArray D2, const Size &imageSize, InputArray R, InputArray tvec, OutputArray R1, OutputArray R2, OutputArray P1, OutputArray P2, OutputArray Q, int flags, const Size &newImageSize=Size(), double balance=0.0, double fov_scale=1.0)
 鱼眼相机模型的立体校正。
 
void cv::stereoRectify (InputArray cameraMatrix1, InputArray distCoeffs1, InputArray cameraMatrix2, InputArray distCoeffs2, Size imageSize, InputArray R, InputArray T, OutputArray R1, OutputArray R2, OutputArray P1, OutputArray P2, OutputArray Q, int flags=CALIB_ZERO_DISPARITY, double alpha=-1, Size newImageSize=Size(), Rect *validPixROI1=0, Rect *validPixROI2=0)
 计算已标定立体摄像机每个头的校正变换。
 
bool cv::stereoRectifyUncalibrated (InputArray points1, InputArray points2, InputArray F, Size imgSize, OutputArray H1, OutputArray H2, double threshold=5)
 计算未标定立体摄像机的校正变换。
 
void cv::triangulatePoints (InputArray projMatr1, InputArray projMatr2, InputArray projPoints1, InputArray projPoints2, OutputArray points4D)
 此函数通过使用立体摄像机对三维点（齐次坐标）的观测来重建这些点。
 
void cv::undistort (InputArray src, OutputArray dst, InputArray cameraMatrix, InputArray distCoeffs, InputArray newCameraMatrix=noArray())
 变换图像以补偿镜头畸变。
 
void cv::fisheye::undistortImage (InputArray distorted, OutputArray undistorted, InputArray K, InputArray D, InputArray Knew=cv::noArray(), const Size &new_size=Size())
 转换图像以补偿鱼眼镜头畸变。
 
void cv::undistortImagePoints (InputArray src, OutputArray dst, InputArray cameraMatrix, InputArray distCoeffs, TermCriteria=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 0.01))
 计算畸变校正后的图像点位置。
 
void cv::fisheye::undistortPoints (InputArray distorted, OutputArray undistorted, InputArray K, InputArray D, InputArray R=noArray(), InputArray P=noArray(), TermCriteria criteria=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 10, 1e-8))
 使用鱼眼模型对 2D 点进行去畸变。
 
void cv::undistortPoints (InputArray src, OutputArray dst, InputArray cameraMatrix, InputArray distCoeffs, InputArray R, InputArray P, TermCriteria criteria)
 
void cv::undistortPoints (InputArray src, OutputArray dst, InputArray cameraMatrix, InputArray distCoeffs, InputArray R=noArray(), InputArray P=noArray())
 根据观测点坐标计算理想点坐标。
 
void cv::validateDisparity (InputOutputArray disparity, InputArray cost, int minDisparity, int numberOfDisparities, int disp12MaxDisp=1)
 使用左右一致性检查来验证视差。矩阵“cost”应通过立体对应算法计算。
 
生成于 2025 年 7 月 3 日 12:14:33，适用于 OpenCV，由 doxygen 1.12.0 生成