SolvePnPRansac是PnP位姿估计鲁棒算法的一种，下面是Opencv 接口函数的描述
/* max 注释 * 函数功能：用ransac的方式求解PnP问题 * * 参数： * [in] _opoints 参考点在世界坐标系下的点集；float or double * [in] _ipoints 参考点在相机像平面的坐标；float or double * [in] _cameraMatrix 相机内参 * [in] _distCoeffs 相机畸变系数 * [out] _rvec 旋转矩阵 * [out] _tvec 平移向量 * [in] useExtrinsicGuess 若果求解PnP使用迭代算法，初始值可以使用猜测的初始值（true），也可以使用解析求解的结果作为初始值（false）。 * [in] iterationsCount Ransac算法的迭代次数，这只是初始值，根据估计外点的概率，可以进一步缩小迭代次数；（此值函数内部是会不断改变的）,所以一开始可以赋一个大的值。 * [in] reprojectionErrr Ransac筛选内点和外点的距离阈值，这个根据估计内点的概率和每个点的均方差（假设误差按照高斯分布）可以计算出此阈值。 * [in] confidence 此值与计算采样（迭代）次数有关。此值代表从n个样本中取s个点，N次采样可以使s个点全为内点的概率。 * [out] _inliers 返回内点的序列。为矩阵形式 * [in] flags 最小子集的计算模型； * SOLVEPNP_ITERATIVE(此方案，最小模型用的EPNP，内点选出之后用了一个迭代)； * SOLVE_P3P(P3P只用在最小模型上，内点选出之后用了一个EPNP) * SOLVE_AP3P(AP3P只用在最小模型上，内点选出之后用了一个EPNP) * SOLVE_EPnP(最小模型上&内点选出之后都采用了EPNP) * 返回值： * 成功返回true，失败返回false； */ bool solvePnPRansac(InputArray _opoints, InputArray _ipoints, InputArray _cameraMatrix, InputArray _distCoeffs, OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess, int iterationsCount, float reprojectionError, double confidence, OutputArray _inliers, int flags)下面是使用例程：
// 自己测试 p3p测位姿算法 #if 1 #include "test_precomp.hpp" void generate3DPointCloud(std::vector<cv::Point3f>& points, cv::Point3f pmin = cv::Point3f(-1, -1, 5), cv::Point3f pmax = cv::Point3f(1, 1, 10)) { cv::RNG rng = cv::theRNG(); // fix the seed to use "fixed" input 3D points for (size_t i = 0; i < points.size(); i++) { float _x = rng.uniform(pmin.x, pmax.x); float _y = rng.uniform(pmin.y, pmax.y); float _z = rng.uniform(pmin.z, pmax.z); points[i] = cv::Point3f(_x, _y, _z); } } void generateCameraMatrix(cv::Mat& cameraMatrix, cv::RNG& rng) { const double fcMinVal = 1e-3; const double fcMaxVal = 100; cameraMatrix.create(3, 3, CV_64FC1); cameraMatrix.setTo(cv::Scalar(0)); cameraMatrix.at<double>(0, 0) = rng.uniform(fcMinVal, fcMaxVal); cameraMatrix.at<double>(1, 1) = rng.uniform(fcMinVal, fcMaxVal); cameraMatrix.at<double>(0, 2) = rng.uniform(fcMinVal, fcMaxVal); cameraMatrix.at<double>(1, 2) = rng.uniform(fcMinVal, fcMaxVal); cameraMatrix.at<double>(2, 2) = 1; } void generateDistCoeffs(cv::Mat& distCoeffs, cv::RNG& rng) { distCoeffs = cv::Mat::zeros(4, 1, CV_64FC1); for (int i = 0; i < 3; i++) distCoeffs.at<double>(i, 0) = rng.uniform(0.0, 1.0e-6); } void generatePose(cv::Mat& rvec, cv::Mat& tvec, cv::RNG& rng) { const double minVal = 1.0e-3; const double maxVal = 1.0; rvec.create(3, 1, CV_64FC1); tvec.create(3, 1, CV_64FC1); for (int i = 0; i < 3; i++) { rvec.at<double>(i, 0) = rng.uniform(minVal, maxVal); tvec.at<double>(i, 0) = rng.uniform(minVal, maxVal / 10); } } int main_p3p() { std::vector<cv::Point3f> points; points.resize(500); generate3DPointCloud(points); std::vector<cv::Mat> rvecs, tvecs; cv::Mat trueRvec, trueTvec; cv::Mat intrinsics, distCoeffs; generateCameraMatrix(intrinsics, cv::RNG()); generateDistCoeffs(distCoeffs, cv::RNG()); generatePose(trueRvec, trueTvec, cv::RNG()); std::vector<cv::Point3f> opoints; opoints = std::vector<cv::Point3f>(points.begin(), points.begin() + 3); std::vector<cv::Point2f> projectedPoints; projectedPoints.resize(opoints.size()); projectPoints(cv::Mat(opoints), trueRvec, trueTvec, intrinsics, distCoeffs, projectedPoints); std::cout << "intrinsics: " << intrinsics << std::endl; std::cout << "distcoeffs: " << distCoeffs << std::endl; std::cout << "trueRvec: " << trueRvec << std::endl; std::cout << "trueTvec: " << trueTvec << std::endl; std::cout << "oPoint: " << opoints << std::endl; std::cout << "projectedPoints: " << projectedPoints << std::endl; std::cout<<"result numbers A: :"<<solveP3P(opoints, projectedPoints, intrinsics, distCoeffs, rvecs, tvecs, cv::SOLVEPNP_AP3P)<<std::endl; //std::cout << "result numbers: :" << solveP3P(opoints, projectedPoints, intrinsics, distCoeffs, rvecs, tvecs, cv::SOLVEPNP_P3P) << std::endl; bool isTestSuccess = false; double error = DBL_MAX; for (unsigned int i = 0; i < rvecs.size() /*&& !isTestSuccess*/; ++i) { double rvecDiff = cvtest::norm(rvecs[i], trueRvec, cv::NORM_L2); double tvecDiff = cvtest::norm(tvecs[i], trueTvec, cv::NORM_L2); isTestSuccess = rvecDiff < 1.0e-4 && tvecDiff < 1.0e-4; error = std::min(error, std::max(rvecDiff, tvecDiff)); std::cout << "i: " << i << std::endl; std::cout << "error: " << error << std::endl; std::cout << "rvec: " << rvecs[i] << std::endl; } system("pause"); return 0; } int main() { std::vector<cv::Point3f> points; points.resize(500); generate3DPointCloud(points); std::vector<cv::Mat> rvecs, tvecs; cv::Mat trueRvec, trueTvec; cv::Mat intrinsics, distCoeffs; generateCameraMatrix(intrinsics, cv::RNG()); generateDistCoeffs(distCoeffs, cv::RNG()); generatePose(trueRvec, trueTvec, cv::RNG()); std::vector<cv::Point3f> opoints; //opoints = std::vector<cv::Point3f>(points.begin(), points.begin() + 4); opoints = std::vector<cv::Point3f>(points.begin(), points.end()); std::vector<cv::Point2f> projectedPoints; projectedPoints.resize(opoints.size()); projectPoints(cv::Mat(opoints), trueRvec, trueTvec, intrinsics, distCoeffs, projectedPoints); cv::RNG rng = cv::RNG(); for (size_t i = 0; i < projectedPoints.size(); i++) { if (i % 100 == 0) { projectedPoints[i] = projectedPoints[rng.uniform(0, (int)points.size() - 1)]; } } std::cout << "intrinsics: " << intrinsics << std::endl; std::cout << "distcoeffs: " << distCoeffs << std::endl; std::cout << "trueRvec: " << trueRvec << std::endl; std::cout << "trueTvec: " << trueTvec << std::endl; //std::cout << "oPoint: " << opoints << std::endl; //std::cout << "projectedPoints: " << projectedPoints << std::endl; //solveP3P(opoints, projectedPoints, intrinsics, distCoeffs, rvecs, tvecs, cv::SOLVEPNP_AP3P); cv::Mat rvec, tvec; solvePnP(opoints, projectedPoints, intrinsics, distCoeffs, rvec, tvec, false,cv::SOLVEPNP_EPNP); std::cout << rvec <<"---" <<norm(rvec-trueRvec)<<std::endl; std::cout << tvec << std::endl; std::cout << "---------------Ransac--------------------"<< std::endl; solvePnPRansac(opoints, projectedPoints, intrinsics, distCoeffs, rvec, tvec,false,100,2); std::cout << rvec << "---" << norm(rvec - trueRvec) << std::endl; std::cout << tvec << std::endl; system("pause"); } #endif文章来源: SolvePnPRansac位姿估计算法