Question

我一直在尝试使用OpenCV stereoRectifyUncalibrated纠正和构建一对图像的差异，但是我没有得到很好的结果。我的代码是：

template<class T>
T convertNumber(string& number)
{
    istringstream ss(number);
    T t;
    ss >> t;
    return t;
}

void readPoints(vector<Point2f>& points, string filename)
{
    fstream filest(filename.c_str(), ios::in);
    string line;

    assert(filest != NULL);

    getline(filest, line);
    do{
        int posEsp = line.find_first_of(' ');
        string posX = line.substr(0, posEsp);
        string posY = line.substr(posEsp+1, line.size() - posEsp);

        float X = convertNumber<float>(posX);
        float Y = convertNumber<float>(posY);

        Point2f pnt = Point2f(X, Y);
        points.push_back(pnt);
        getline(filest, line);
    }while(!filest.eof());

    filest.close();
}

void drawKeypointSequence(Mat lFrame, Mat rFrame, vector<KeyPoint>& lKeyp, vector<KeyPoint>& rKeyp)
{
    namedWindow("prevFrame", WINDOW_AUTOSIZE);
    namedWindow("currFrame", WINDOW_AUTOSIZE);
    moveWindow("prevFrame", 0, 300);
    moveWindow("currFrame", 650, 300);
    Mat rFrameAux;
    rFrame.copyTo(rFrameAux);
    Mat lFrameAux;
    lFrame.copyTo(lFrameAux);

    int size = rKeyp.size();
    for(int i=0; i<size; i++)
    {
        vector<KeyPoint> drawRightKeyp;
        vector<KeyPoint> drawleftKeyp;

        drawRightKeyp.push_back(rKeyp[i]);
        drawleftKeyp.push_back(lKeyp[i]);

        cout << rKeyp[i].pt << " <<<>>> " << lKeyp[i].pt << endl;

        drawKeypoints(rFrameAux, drawRightKeyp, rFrameAux, Scalar::all(255), DrawMatchesFlags::DRAW_OVER_OUTIMG);
        drawKeypoints(lFrameAux, drawleftKeyp, lFrameAux, Scalar::all(255), DrawMatchesFlags::DRAW_OVER_OUTIMG);

        imshow("currFrame", rFrameAux);
        imshow("prevFrame", lFrameAux);
        waitKey(0);
    }
    imwrite("RightKeypFrame.jpg", rFrameAux);
    imwrite("LeftKeypFrame.jpg", lFrameAux);
}
int main(int argc, char* argv[])
{
    StereoBM stereo(StereoBM::BASIC_PRESET, 16*5, 21);
    double ndisp = 16*4;
    assert(argc == 5);
    string rightImgFilename(argv[1]);       // Right image (current frame)
    string leftImgFilename(argv[2]);        // Left image (previous frame)
    string rightPointsFilename(argv[3]);    // Right image points file
    string leftPointsFilename(argv[4]);     // Left image points file

    Mat rightFrame = imread(rightImgFilename.c_str(), 0);
    Mat leftFrame = imread(leftImgFilename.c_str(), 0);

    vector<Point2f> rightPoints;
    vector<Point2f> leftPoints;

    vector<KeyPoint> rightKeyp;
    vector<KeyPoint> leftKeyp;

    readPoints(rightPoints, rightPointsFilename);
    readPoints(leftPoints, leftPointsFilename);
    assert(rightPoints.size() == leftPoints.size());

    KeyPoint::convert(rightPoints, rightKeyp);
    KeyPoint::convert(leftPoints, leftKeyp);

    // Desenha os keypoints sequencialmente, de forma a testar a consistência do matching
    drawKeypointSequence(leftFrame, rightFrame, leftKeyp, rightKeyp);

    Mat fundMatrix = findFundamentalMat(leftPoints, rightPoints, CV_FM_8POINT);
    Mat homRight;
    Mat homLeft;
    Mat disp16 = Mat(rightFrame.rows, leftFrame.cols, CV_16S);
    Mat disp8 = Mat(rightFrame.rows, leftFrame.cols, CV_8UC1);
    stereoRectifyUncalibrated(leftPoints, rightPoints, fundMatrix, rightFrame.size(), homLeft, homRight);

    warpPerspective(rightFrame, rightFrame, homRight, rightFrame.size());
    warpPerspective(leftFrame, leftFrame, homLeft, leftFrame.size());


    namedWindow("currFrame", WINDOW_AUTOSIZE);
    namedWindow("prevFrame", WINDOW_AUTOSIZE);
    moveWindow("currFrame", 650, 300);
    moveWindow("prevFrame", 0, 300);
    imshow("currFrame", rightFrame);
    imshow("prevFrame", leftFrame);

    imwrite("RectfRight.jpg", rightFrame);
    imwrite("RectfLeft.jpg", leftFrame);

    waitKey(0);

    stereo(rightFrame, leftFrame, disp16, CV_16S);

    disp16.convertTo(disp8, CV_8UC1, 255/ndisp);
    FileStorage file("disp_map.xml", FileStorage::WRITE);
    file << "disparity" << disp8;
    file.release();
    imshow("disparity", disp8);
    imwrite("disparity.jpg", disp8);
    moveWindow("disparity", 0, 0);

    waitKey(0);
}

drawKeyPoint序列是我直观地检查两个图像的点的一致性的方式。通过按顺序绘制每个关键点，我可以确定图像A上的关键点i是图像B上的关键点i。

我也尝试过使用ndisp参数，但它没有多大帮助。

我尝试了以下一对图片：

得到以下纠正对：

最后，以下视差图

正如你所看到的那样，非常糟糕。我还使用以下stereoRectifyUncalibrated示例尝试了同一对图像：http://programmingexamples.net/wiki/OpenCV/WishList/StereoRectifyUncalibrated和来自opencv教程代码示例的SBM_Sample.cpp来构建视差图，并得到了非常相似的结果。

我正在使用opencv 2.4

提前致谢！

Answer 1

除了可能的校准问题，您的图像显然缺少一些纹理，以便立体块匹配工作。该算法将在平坦（非tetxured）零件上看到许多模糊和太大的差异。

但请注意，关键点似乎匹配得很好，所以即使整流输出看起来很奇怪，也可能是正确的。

您可以根据Middlebury stereo page中的标准图像测试代码，以进行完整性检查。

Answer 2

我建议使用棋盘进行立体声校准，或者使用棋盘拍摄多张照片并在计算机上使用stereocalibrate.cpp。我这样说是因为你使用stereorectifyuncalibrated，虽然算法不需要知道摄像机的内部参数，但它在很大程度上取决于极线几何。因此，如果相机镜头有明显的失真，最好在计算基本矩阵并调用此功能之前进行校正。例如，可以使用calibrateCamera()分别为立体相机的每个头估计失真系数。然后，可以使用undistort()更正图像，或者只使用undistortPoints()更正点坐标。

opencv stereoRectifyUncalibrated的问题

2 个答案: