OpenNIDataGet 获取点云数据

运行后，采集的数据保存到：E:\OpenCVData目录下的color和depth文件夹下。
接下来要求参数：内参 外参 这些参数最好优化后使用精度高

如何得到+保存格式

yaml

 

保存文件格式：

1. 索引

2. 数据

3. 数据

4.。。。

其中copenni类是一个OPENNI对象类

#include <XnCppWrapper.h>
#include <QtGui/QtGui>
#include <iostream>

using namespace xn;
using namespace std;

class COpenNI
{
public:
    ~COpenNI() {
        context.Release();//释放空间
    }
    bool Initial() {
        //初始化
        status = context.Init();
        if(CheckError("Context initial failed!")) {
            return false;
        }
        context.SetGlobalMirror(true);//设置镜像
        //产生图片node
        status = image_generator.Create(context);
        if(CheckError("Create image generator  error!")) {
            return false;
        }
        //产生深度node
        status = depth_generator.Create(context);
        if(CheckError("Create depth generator  error!")) {
            return false;
        }
        //视角校正
        status = depth_generator.GetAlternativeViewPointCap().SetViewPoint(image_generator);
        if(CheckError("Can't set the alternative view point on depth generator")) {
            return false;
        }

        return true;

    }

    bool Start() {
        status = context.StartGeneratingAll();
        if(CheckError("Start generating error!")) {
            return false;
        }
        return true;
    }

    bool UpdateData() {
        status = context.WaitNoneUpdateAll();
        if(CheckError("Update date error!")) {
            return false;
        }
        //获取数据
        image_generator.GetMetaData(image_metadata);
        depth_generator.GetMetaData(depth_metadata);

        return true;
    }

public:
    DepthMetaData depth_metadata;
    ImageMetaData image_metadata;

private:
    //该函数返回真代表出现了错误，返回假代表正确
    bool CheckError(const char* error) {
        if(status != XN_STATUS_OK ) {
            QMessageBox::critical(NULL, error, xnGetStatusString(status));
            cerr << error << ": " << xnGetStatusString( status ) << endl;
            return true;
        }
        return false;
    }

private:
    XnStatus    status;
    Context     context;
    DepthGenerator  depth_generator;
    ImageGenerator  image_generator;
};

main是主类

#include <QtCore/QCoreApplication>

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <opencv2/core/core.hpp>
#include "copenni.cpp"

#include <iostream>

using namespace cv;
using namespace xn;

string Int_to_String(int n);

int main (int argc, char **argv)
{
    COpenNI openni;
    if(!openni.Initial())
        return 1;

    namedWindow("color image", CV_WINDOW_AUTOSIZE);
    namedWindow("color edge detect", CV_WINDOW_AUTOSIZE);
    namedWindow("depth image", CV_WINDOW_AUTOSIZE);
    namedWindow("depth edge detect", CV_WINDOW_AUTOSIZE);

    if(!openni.Start())
        return 1;
    char key=0;
    int i=0, j=0;
    while((i==0)) {//key!=27
        if(!openni.UpdateData()) {
            return 1;
        }
        /*获取并显示色彩图像*/
        Mat color_image_src(openni.image_metadata.YRes(), openni.image_metadata.XRes(),
                            CV_8UC3, (char *)openni.image_metadata.Data());
        Mat color_image;
        cvtColor(color_image_src, color_image, CV_RGB2BGR);
        imshow("color image", color_image);

        //保存彩色图像
        j = i++;
        string str1 = "E:\\OpenCVData\\color\\";
        string str11 = "E:\\OpenCVData\\depth\\";
        string str2 = ".jpg";
        string str3 = str1 + Int_to_String(j) + str2; //彩色图像名称
        char * cstr = new char [str2.length()+1];
        std::strcpy (cstr, str2.c_str());
        cout<<cstr;
        
        //cvSaveImage(cstr, color_image);
        imwrite(str3, color_image);

        /*对色彩图像进行canny边缘检测并显示*/
        Mat color_image_gray, color_image_edge;
        cvtColor(color_image_src, color_image_gray, CV_RGB2GRAY);//因为在进行边缘检测的时候只能使用灰度图像
        Canny(color_image_gray, color_image_edge, 5, 100);
        imshow("color edge detect", color_image_edge);

        /*获取并显示深度图像*/
        Mat depth_image_src(openni.depth_metadata.YRes(), openni.depth_metadata.XRes(),
                            CV_16UC1, (char *)openni.depth_metadata.Data());//因为kinect获取到的深度图像实际上是无符号的16位数据
        Mat depth_image, depth_image_edge;
        depth_image_src.convertTo(depth_image, CV_8U, 255.0/8000); //对齐？
        imshow("depth image", depth_image);

        //保存深度图像
        string str4 = str11 + Int_to_String(j) + str2; //深度图像名称
        imwrite(str4, depth_image);


        /*计算深度图像的canny边缘并显示*/
        Canny(depth_image, depth_image_edge, 5, 100);
        imshow("depth edge detect", depth_image_edge);
        key=cvWaitKey(30);
    }

}

string Int_to_String(int n)
{
ostringstream stream;
stream<<n;  //n为int类型
return stream.str();
}