两幅图的RGB+Depth点云拼接

心已赠人 2022-12-11 15:11 166阅读 0赞

目标： **输入两幅图的RGB和Depth深度图，输出一个拼接的pcd点云图**

两幅图的RBG+Depth点云拼接主程序：

/*************************************************************************
    	> File Name: src/jointPointCloud.cpp
    	> Author: Xiang gao
    	> Mail: gaoxiang12@mails.tsinghua.edu.cn 
    	> Created Time: 2015年07月22日 星期三 20时46分08秒
     ************************************************************************/
    
    #include<iostream>
    using namespace std;
    
    #include "slamBase.h"
    
    #include <opencv2/core/eigen.hpp>
    
    #include <pcl/common/transforms.h>
    #include <pcl/visualization/cloud_viewer.h>
    
    // Eigen !
    #include <Eigen/Core>
    #include <Eigen/Geometry>
    
    int main( int argc, char** argv )
    {
        //本节要拼合data中的两对图像
        ParameterReader pd;
        // 声明两个帧，FRAME结构请见include/slamBase.h
        FRAME frame1, frame2;
        
        //读取图像
        frame1.rgb = cv::imread( "./data/rgb1.png" );
        frame1.depth = cv::imread( "./data/depth1.png", -1);
        frame2.rgb = cv::imread( "./data/rgb2.png" );
        frame2.depth = cv::imread( "./data/depth2.png", -1 );
    
        // 提取特征并计算描述子
        cout<<"extracting features"<<endl;
        string detecter = pd.getData( "detector" );
        string descriptor = pd.getData( "descriptor" );
    
        computeKeyPointsAndDesp( frame1, detecter, descriptor );
        computeKeyPointsAndDesp( frame2, detecter, descriptor );
    
        // 相机内参
        CAMERA_INTRINSIC_PARAMETERS camera;
        camera.fx = atof( pd.getData( "camera.fx" ).c_str());
        camera.fy = atof( pd.getData( "camera.fy" ).c_str());
        camera.cx = atof( pd.getData( "camera.cx" ).c_str());
        camera.cy = atof( pd.getData( "camera.cy" ).c_str());
        camera.scale = atof( pd.getData( "camera.scale" ).c_str() );
    
        cout<<"solving pnp"<<endl;
        // 求解pnp
        RESULT_OF_PNP result = estimateMotion( frame1, frame2, camera ); //john:获得frame1相对于frame2的旋转和平移(T=(R,t))
    
        cout<<result.rvec<<endl<<result.tvec<<endl;
    
        // 处理result
        // 将旋转向量转化为旋转矩阵
        cv::Mat R;
        cv::Rodrigues( result.rvec, R );
        Eigen::Matrix3d r;
        cv::cv2eigen(R, r);
      
        // 将平移向量和旋转矩阵转换成变换矩阵
        Eigen::Isometry3d T = Eigen::Isometry3d::Identity();
    
        Eigen::AngleAxisd angle(r);
        cout<<"translation"<<endl;
        Eigen::Translation<double,3> trans(result.tvec.at<double>(0,0), result.tvec.at<double>(0,1), result.tvec.at<double>(0,2));
        T = angle;
        T(0,3) = result.tvec.at<double>(0,0); 
        T(1,3) = result.tvec.at<double>(0,1); 
        T(2,3) = result.tvec.at<double>(0,2);
    
        // 转换点云
        cout<<"converting image to clouds"<<endl;
        PointCloud::Ptr cloud1 = image2PointCloud( frame1.rgb, frame1.depth, camera );
        PointCloud::Ptr cloud2 = image2PointCloud( frame2.rgb, frame2.depth, camera );
    
        // 合并点云
        cout<<"combining clouds"<<endl;
        PointCloud::Ptr output (new PointCloud());
        pcl::transformPointCloud( *cloud1, *output, T.matrix() ); //john:将frame1对应的点云使用T, 变换到frame2对应的视角下? 
        *output += *cloud2;                                       // 都是三维空间点，为什么不能直接相加??采用不同的世界坐标系？
        pcl::io::savePCDFile("data/result.pcd", *output);
        cout<<"Final result saved."<<endl;
    
        pcl::visualization::CloudViewer viewer( "viewer" );
        viewer.showCloud( output );
        while( !viewer.wasStopped() )
        {
            
        }
        return 0;
    }

参考：[一起做RGB-D SLAM (4)][RGB-D SLAM _4]

完整代码：[https://github.com/gaoxiang12/rgbd-slam-tutorial-gx][https_github.com_gaoxiang12_rgbd-slam-tutorial-gx] Part IV src/

[RGB-D SLAM _4]: https://www.cnblogs.com/gaoxiang12/p/4669490.html
[https_github.com_gaoxiang12_rgbd-slam-tutorial-gx]: https://github.com/gaoxiang12/rgbd-slam-tutorial-gx