Three-dimensional reconstruction based on OpenCV (4)-camera pose restoration and three-dimensional reconstruction

v When we successfully build viz, we can use the convenience provided by the 3D effect to further carry out some 3D operations.

在这个动画中，注意图片后面的那个黑线，对应的是相机的位置。
/------------------------------------------------------------------------------------------
This file contains material supporting chapter 11 of the book:
OpenCV3 Computer Vision Application Programming Cookbook
Third Edition
by Robert Laganiere, Packt Publishing, 2016.
This program is free software; permission is hereby granted to use, copy, modify,
and distribute this source code, or portions thereof, for any purpose, without fee,
subject to the restriction that the copyright notice may not be removed
or altered from any source or altered source distribution.
The software is released on an as-is basis and without any warranties of any kind.
In particular, the software is not guaranteed to be fault-tolerant or free from failure.
The author disclaims all warranties with regard to this software, any use,
and any consequent failure, is purely the responsibility of the user.
Copyright © 2016 Robert Laganiere, www.laganiere.name
*------------------------------------------------------------------------------------------*/

#include "stdafx.h"
#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/viz.hpp>
#include <opencv2/calib3d.hpp>
#include <iostream>
int main()
{
    // Read the camera calibration parameters
    cv::Mat cameraMatrix;
    cv::Mat cameraDistCoeffs;
    cv::FileStorage fs("calib.xml", cv::FileStorage::READ);
    fs["Intrinsic"] >> cameraMatrix;
    fs["Distortion"] >> cameraDistCoeffs;
    std::cout << " Camera intrinsic: " << cameraMatrix.rows << "x" << cameraMatrix.cols << std::endl;
    std::cout << cameraMatrix.at<double>(0, 0) << " " << cameraMatrix.at<double>(0, 1) << " " << cameraMatrix.at<double>(0, 2) << std::endl;
    std::cout << cameraMatrix.at<double>(1, 0) << " " << cameraMatrix.at<double>(1, 1) << " " << cameraMatrix.at<double>(1, 2) << std::endl;
    std::cout << cameraMatrix.at<double>(2, 0) << " " << cameraMatrix.at<double>(2, 1) << " " << cameraMatrix.at<double>(2, 2) << std::endl << std::endl;
    cv::Matx33d cMatrix(cameraMatrix);
    // Input image points
    std::vector<cv::Point2f> imagePoints;
    imagePoints.push_back(cv::Point2f(136, 113));
    imagePoints.push_back(cv::Point2f(379, 114));
    imagePoints.push_back(cv::Point2f(379, 150));
    imagePoints.push_back(cv::Point2f(138, 135));
    imagePoints.push_back(cv::Point2f(143, 146));
    imagePoints.push_back(cv::Point2f(381, 166));
    imagePoints.push_back(cv::Point2f(345, 194));
    imagePoints.push_back(cv::Point2f(103, 161));
    // Input object points
    std::vector<cv::Point3f> objectPoints;
    objectPoints.push_back(cv::Point3f(0, 45, 0));
    objectPoints.push_back(cv::Point3f(242.5, 45, 0));
    objectPoints.push_back(cv::Point3f(242.5, 21, 0));
    objectPoints.push_back(cv::Point3f(0, 21, 0));
    objectPoints.push_back(cv::Point3f(0, 9, -9));
    objectPoints.push_back(cv::Point3f(242.5, 9, -9));
    objectPoints.push_back(cv::Point3f(242.5, 9, 44.5));
    objectPoints.push_back(cv::Point3f(0, 9, 44.5));
    // Read image
    cv::Mat image = cv::imread("e:/template/bench2.jpg");
    // Draw image points
    for (int i = 0; i < 8; i++) {
        cv::circle(image, imagePoints[i], 3, cv::Scalar(0, 0, 0),2);
    }
    cv::imshow("An image of a bench", image);
    // Create a viz window
    cv::viz::Viz3d visualizer("Viz window");
    visualizer.setBackgroundColor(cv::viz::Color::white());
    /// Construct the scene
    // Create a virtual camera
    cv::viz::WCameraPosition cam(cMatrix,  // matrix of intrinsics
        image,    // image displayed on the plane
        30.0,     // scale factor
        cv::viz::Color::black());
    // Create a virtual bench from cuboids
    cv::viz::WCube plane1(cv::Point3f(0.0, 45.0, 0.0), 
        cv::Point3f(242.5, 21.0, -9.0), 
        true,  // show wire frame 
        cv::viz::Color::blue());
    plane1.setRenderingProperty(cv::viz::LINE_WIDTH, 4.0);
    cv::viz::WCube plane2(cv::Point3f(0.0, 9.0, -9.0), 
        cv::Point3f(242.5, 0.0, 44.5), 
        true,  // show wire frame 
        cv::viz::Color::blue());
    plane2.setRenderingProperty(cv::viz::LINE_WIDTH, 4.0);
    // Add the virtual objects to the environment
    visualizer.showWidget("top", plane1);
    visualizer.showWidget("bottom", plane2);
    visualizer.showWidget("Camera", cam);
    // Get the camera pose from 3D/2D points
    cv::Mat rvec, tvec;
    cv::solvePnP(objectPoints, imagePoints,      // corresponding 3D/2D pts 
        cameraMatrix, cameraDistCoeffs, // calibration 
        rvec, tvec);                    // output pose
    std::cout << " rvec: " << rvec.rows << "x" << rvec.cols << std::endl;
    std::cout << " tvec: " << tvec.rows << "x" << tvec.cols << std::endl;
    cv::Mat rotation;
    // convert vector-3 rotation
    // to a 3x3 rotation matrix
    cv::Rodrigues(rvec, rotation);
    // Move the bench    
    cv::Affine3d pose(rotation, tvec);
    visualizer.setWidgetPose("top", pose);
    visualizer.setWidgetPose("bottom", pose);
    // visualization loop
    while(cv::waitKey(100)==-1 && !visualizer.wasStopped())
    {
        visualizer.spinOnce(1,     // pause 1ms 
            true); // redraw
    }
    return 0;
}

For the 3D reconstruction, I also run the example of a successful book:

From Wiz

Attachment list

Current direction: image stitching and fusion, image recognition Contact: [email protected]