OPENCV之从calibrateCamera到solvePnP（一）

写这篇文章其实主要是给入门者参考的，没有技术含量。主要是看到网上流传有各种疑问和答案，这里用自己的理解总结一下，一步一步从单目标定到重建写一下。

开发环境VS2013+OPENCV2.4.9

文章围绕OPENCV原函数C++版本的调用展开，构造输入和输出参数。

首先看标定

原理不再说明。
第一个参数物点是由自己构造的一系列点三维坐标。
以下图为例

vector<vector<Point3f> > calcBoardCornerPositions(int gridW, int gridH, float squareSize, int imagesCount){    vector<vector<Point3f> > objectPoints(imagesCount);    for (int k = 0; k <imagesCount; k++) {        objectPoints[k] = vector<Point3f>(0);        for (int i = 0; i < gridH; i++)            for (int j = 0; j < gridW; j++)                objectPoints[k].push_back(Point3f(float(j*squareSize), float(i*squareSize), 0));    }    return objectPoints;}vector<vector<Point3f> > objectPoints = calcBoardCornerPositions(grids.width, grids.height, 260, imagePoints.size());

这里 Size grids(9, 6);//代表棋盘点的个数
int Grids_Size = 260;//代表棋盘格子宽度（0.1mm)
Z坐标设为0.
棋盘的长宽可以不同，构造方法类似。
以上得到了第一个参数。

第二个参数像点，代表在图上检测到的角点像素坐标。

vector<vector<Point2f> > imagePoints;vector<int> usefulImgIndeces;for (int i = 0; i <20; i++) {    vector<Point2f> corners;    bool found = findChessboardCorners(images[i], grids, corners, CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE + CALIB_CB_FAST_CHECK);    if (found) {        usefulImgIndeces.push_back(i);        Mat gray;        cvtColor(images[i], gray, CV_BGR2GRAY);        cornerSubPix(gray, corners, Size(11, 11), Size(-1, -1),            TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, 0.1));//0.1为精度        imagePoints.push_back(corners);        if (true) {            drawChessboardCorners(images[i], grids, Mat(corners), found);            //imshow("chessboard" + to_string(i), images[i]);            //waitKey(200);        }    }}

以上得到第二个参数。
对于findChessboardCorners函数，OPENCV内部使用cvCheckChessboard先判断是否有棋盘，算法阈值由低到高，决定平均亮度较低的时候检测棋盘较快。
在findChessboardCorners中同样调用了

        cvFindCornerSubPix( gray, out_corners, pattern_size.width*pattern_size.height,            cvSize(wsize, wsize), cvSize(-1,-1), cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 15, 0.1));

精确寻找角点。再外部再调用其实意义不大，不过耗时也不多，可把精度提高再迭代几次。

以上得到两个参数了，注意两个参数的类型vector

vector<Mat> rvecs, tvecs; Mat  cameraMatrix; Mat distCoeffs;

再后面的参数可以不用管了，网上很多解释，有特殊需求的可以查一查其含义。

最后使用FileStorage保存参数。

FileStorage fs;fs.open("result.xml", FileStorage::WRITE);fs << "cameraMatrix" << cameraMatrix;fs << "distCoeffs" << distCoeffs;fs.release();

完整代码

#include <cv.h>#include <highgui.h>#include <iostream>using namespace std;using namespace cv;vector<vector<Point3f> > calcBoardCornerPositions(int gridW, int gridH, float squareSize, int imagesCount){    vector<vector<Point3f> > objectPoints(imagesCount);    for (int k = 0; k <imagesCount; k++) {        objectPoints[k] = vector<Point3f>(0);        for (int i = 0; i < gridH; i++)            for (int j = 0; j < gridW; j++)                objectPoints[k].push_back(Point3f(float(j*squareSize), float(i*squareSize), 0));    }    return objectPoints;}int i = 0; Mat frame;void onMouse(int event, int x, int y, int flags, void* userdata){    if (event == 1)        imwrite(to_string(i++) + ".jpg", frame);}int main(){    VideoCapture cap(0);    //cap.set(CV_CAP_PROP_FRAME_WIDTH, 1920);    //cap.set(CV_CAP_PROP_FRAME_HEIGHT, 1080);    char key;    if (!cap.isOpened()) return -1;    namedWindow("frame", 0);    cap >> frame;//该镜头第一帧可能为空白    for (;i<20;)    {        cap >> frame;        setMouseCallback("frame", onMouse);        key = waitKey(20);        if (key == ' ')        {            imwrite(to_string(i++) + ".jpg", frame);        }        if (key == 'q')break;        imshow("frame", frame);    }vector<Mat> images;for (int i = 0; i <20; i++) {    images.push_back(imread(to_string(i)+".jpg"));}//Size grids(7, 5);Size grids(9, 6);int Grids_Size = 260;vector<vector<Point2f> > imagePoints;vector<int> usefulImgIndeces;for (int i = 0; i <20; i++) {    vector<Point2f> corners;    bool found = findChessboardCorners(images[i], grids, corners, CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE + CALIB_CB_FAST_CHECK);    if (found) {        usefulImgIndeces.push_back(i);        Mat gray;        cvtColor(images[i], gray, CV_BGR2GRAY);        cornerSubPix(gray, corners, Size(11, 11), Size(-1, -1),            TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, 0.1));//0.1为精度        imagePoints.push_back(corners);        if (true) {            drawChessboardCorners(images[i], grids, Mat(corners), found);            //imshow("chessboard" + to_string(i), images[i]);            //waitKey(200);        }    }}if (usefulImgIndeces.empty()) {    cout << "no chessboard found." << endl;    return false;}vector<vector<Point3f> > objectPoints = calcBoardCornerPositions(grids.width, grids.height, Grids_Size, imagePoints.size());Size imageSize = images[0].size(); /*cout << images.size() << endl; cout << imagePoints.size() << endl; waitKey(100000);*/vector<Mat> rvecs, tvecs; Mat  cameraMatrix; Mat distCoeffs; Mat Output;double rms = calibrateCamera(objectPoints, imagePoints, imageSize, cameraMatrix, distCoeffs, rvecs, tvecs);FileStorage fs;fs.open("result.xml", FileStorage::WRITE);fs << "cameraMatrix" << cameraMatrix;fs << "distCoeffs" << distCoeffs;fs.release();for (int i = 0; i < 20; i++){    undistort(images[i], Output, cameraMatrix, distCoeffs);    namedWindow("out" + to_string(i),0);    imshow("out"+to_string(i), images[i]);    //imshow("qqq", Output);    waitKey(200);}waitKey();cout << cameraMatrix << endl;cout << distCoeffs << endl;    waitKey();    return 0;}

下篇进入下一阶段。