SLAM练习题（八）——单应矩阵

SLAM 学习笔记

文章目录

单应矩阵
总结：

单应矩阵

以下题目来自计算机视觉life从零开始一起学习SLAM系列
题目: 利用OpenCV编程实现虚拟广告牌的效果。提供两张图,一张是“计算机视觉life”公众号的logo,另外一张是带广告牌的原图,请用单应矩阵实现将原图中广告牌替换为提供的logo的效果。要求通过鼠标点击来选择要替换的广告牌的四个顶点。
代码框架及图片见: 链接:https://pan.baidu.com/s/1uRsBJWahU7uQ7nOk1R49ow 密码:xn5l
参考答案:

#include <opencv2/opencv.hpp>

using namespace cv;
using namespace std;

struct userdata{
    Mat im;
    vector<Point2f> points;
};

void mouseHandler(int event, int x, int y, int flags, void* data_ptr)
{
    if  ( event == EVENT_LBUTTONDOWN )
    {
        userdata *data = ((userdata *) data_ptr);
        circle(data->im, Point(x,y),3,Scalar(0,255,255), 5, CV_AA);
        imshow("Image", data->im);
        if (data->points.size() < 4)
        {
            data->points.push_back(Point2f(x,y));
        }
    }
    
}

int main( int argc, char** argv)
{

    // Read in the image.
    //Mat im_src = imread("first-image.jpg");
    Mat im_src = imread("cvlife.jpg");
    Size size = im_src.size();
   
    // Create a vector of points.
    vector<Point2f> pts_src;
    pts_src.push_back(Point2f(0,0));
    pts_src.push_back(Point2f(size.width - 1, 0));
    pts_src.push_back(Point2f(size.width - 1, size.height -1));
    pts_src.push_back(Point2f(0, size.height - 1 ));
    
    // Destination image
    //Mat im_dst = imread("times-square.jpg");
    Mat im_dst = imread("ad.jpg");

    // Set data for mouse handler
    Mat im_temp = im_dst.clone();
    userdata data;
    data.im = im_temp;

    //show the image
    imshow("Image", im_temp);
    
    cout << "Click on four corners of a billboard and then press ENTER" << endl;
    //set the callback function for any mouse event
    setMouseCallback("Image", mouseHandler, &data);
    waitKey(0); // 暂停直到按下enter
    
    // ----------  开始你的代码  --------------
    //  计算四个角点和目标图区域对应角点的 Homegraphy
    Mat homography = findHomography(pts_src, data.points);

    //  用H对原图做变换
    warpPerspective(im_src,im_temp,homography, im_temp.size()); // 注意输出图片的尺寸，一定要和im_dst的尺寸一致。
    //imshow("test",im_temp);
    //  提取鼠标点击的四个角点
    Point pts_dst[4];
    for (int i = 0; i < 4; i++)
    {
        pts_dst[i] = data.points[i];
    }
    //  把目标中对应区域像素值设置为0
    fillConvexPoly(im_dst,pts_dst,4,Scalar(0),CV_AA);
    //  把原图叠加到目标图上
    im_dst = im_dst + im_temp;

    // ----------  结束你的代码  --------------
    // Display image.
    imshow("Image", im_dst);
    waitKey(0);

    return 0;
}

效果：

在这里插入图片描述

附：CMakeLists.txt

cmake_minimum_required(VERSION 2.8)
project(012_practice)

set(CMAKE_BUILD_TYPE "Release")
set(CMAKE_CXX_FLAGS "-std=c++11")

# 添加OpenCV
find_package(OpenCV REQUIRED)
include_directories(${OpenCV_INCLUDE_DIRS})

add_executable(virtual-billboard virtual-billboard.cpp)
target_link_libraries(virtual-billboard ${OpenCV_LIBS})

总结：

单应矩阵：单应矩阵描述的就是同一个平面的点在不同图像之间的映射关系。参考

$\begin{array}{l} \left(\begin{array}{l} u_{1} \\ v_{1} \\ 1 \end{array}\right)=M_{1}\left(\begin{array}{c} x_{w} \\ y_{w} \\ 1 \end{array}\right),\left(\begin{array}{l} u_{2} \\ v_{2} \\ 1 \end{array}\right)=M_{2}\left(\begin{array}{c} x_{u} \\ y_{w} \\ 1 \end{array}\right) \\ \left(\begin{array}{l} u_{2} \\ v_{2} \\ 1 \end{array}\right)=M_{2} M_{1}^{-1}\left(\begin{array}{c} u_{1} \\ v_{1} \\ 1 \end{array}\right)=H\left(\begin{array}{c} u_{1} \\ v_{1} \\ 1 \end{array}\right) \end{array}$