[naive] triangular mesh的support point选择

一种naive的方法：在图像的边缘上做间隔采样。

int main(int argc, char** argv)
{
    if (argc < 2)
    {
        cout << "usage: ./demo input_image" << endl;
        return -1;
    }

    Mat img = imread(argv[1]);

    if (img.empty())
    {
        cout << "error: image is empty" << endl;
    }

    Mat imgGray, imgBlur, imgEdge;

    cvtColor(img, imgGray, CV_BGR2GRAY);

    blur(imgGray, imgBlur, Size(3, 3));

    double threshold = 10.0;
    Canny(imgBlur, imgEdge, threshold, threshold * 3, 3);

    vector supportPoints;

    uint32_t imgHeight = img.rows;
    uint32_t imgWidth = img.cols;

    uint32_t sampleInterval = 3;
    for (int row = 0; row < imgHeight; row += sampleInterval)
    {
        for (int col = 0; col < imgWidth; col += sampleInterval)
        {
            if (imgEdge.at(row, col) == 255)
            {
                supportPoints.push_back(Point2f(col, row));
            }
        }
    }

    Mat imgSupportPoints = img.clone();

    for (int i = 0; i < supportPoints.size(); i++)
    {
        circle( imgSupportPoints, supportPoints[i], 1, Scalar(0, 0, 255), FILLED, LINE_8, 0 );
    }

    imshow("img with support points", imgSupportPoints);
    waitKey(0);
}