基于C++实现kinect+opencv 获取深度及彩色数据

#include <opencv2/opencv.hpp> #include<iostream>//windows的头文件，必须要，不然NuiApi.h用不了#include <Windows.h>//Kinect for windows 的头文件#include "NuiApi.h" using namespace std;using namespace cv; #include <d3d11.h>  //最远距离(mm)const int MAX_DISTANCE = 3500;//最近距离(mm)const int MIN_DISTANCE = 200; const LONG m_depthWidth = 640;const LONG m_depthHeight = 480;const LONG m_colorWidth = 640;const LONG m_colorHeight = 480;const LONG cBytesPerPixel = 4; int main(){  //彩色图像  Mat image_rgb;  //深度图像  Mat image_depth;   //创建一个MAT  image_rgb.create(480,640,CV_8UC3);  image_depth.create(480,640,CV_8UC1);   //一个KINECT实例指针  INuiSensor* m_pNuiSensor = NULL;   if (m_pNuiSensor != NULL)  {    return 0;  }   //记录当前连接KINECT的数量（为多连接做准备）  int iSensorCount;  //获得当前KINECT的数量  HRESULT hr = NuiGetSensorCount(&iSensorCount);    //按照序列初始化KINETC实例，这里就连接了一个KINECT，所以没有用到循环  hr = NuiCreateSensorByIndex(iSensorCount - 1, &m_pNuiSensor);  //初始化，让其可以接收彩色和深度数据流  hr = m_pNuiSensor->NuiInitialize(NUI_INITIALIZE_FLAG_USES_COLOR | NUI_INITIALIZE_FLAG_USES_DEPTH);   //判断是否出错  if (FAILED(hr))  {    cout<<"NuiInitialize failed"<<endl;    return hr;  }   //彩色图像获取下一帧事件  HANDLE nextColorFrameEvent = CreateEvent(NULL, TRUE, FALSE, NULL);  //彩色图像事件句柄  HANDLE colorStreamHandle = NULL;  //深度图像获取下一帧事件  HANDLE nextDepthFrameEvent = CreateEvent(NULL, TRUE, FALSE, NULL);  //深度图像事件句柄  HANDLE depthStreamHandle = NULL;   //实例打开数据流，这里NUI_IMAGE_TYPE_COLOR表示彩色图像  hr = m_pNuiSensor->NuiImageStreamOpen(NUI_IMAGE_TYPE_COLOR, NUI_IMAGE_RESOLUTION_640x480, 0,2,nextColorFrameEvent,&colorStreamHandle);   if( FAILED( hr ) )//判断是否提取正确  {    cout<<"Could not open color image stream video"<<endl;    m_pNuiSensor->NuiShutdown();    return hr;  }   //实例打开数据流，这里NUI_IMAGE_TYPE_DEPTH表示深度图像  hr = m_pNuiSensor->NuiImageStreamOpen(NUI_IMAGE_TYPE_DEPTH, NUI_IMAGE_RESOLUTION_640x480, 0,2, nextDepthFrameEvent, &depthStreamHandle);   if( FAILED( hr ) )//判断是否提取正确  {    cout<<"Could not open color image stream video"<<endl;    m_pNuiSensor->NuiShutdown();    return hr;  }     cv::namedWindow("depth", CV_WINDOW_AUTOSIZE);  moveWindow("depth",300,600);  cv::namedWindow("colorImage",CV_WINDOW_AUTOSIZE);  moveWindow("colorImage",0,200);   while (1)  {    NUI_IMAGE_FRAME pImageFrame_rgb;    NUI_IMAGE_FRAME pImageFrame_depth;     //无限等待新的彩色数据，等到后返回    if (WaitForSingleObject(nextColorFrameEvent, 0) == 0)    {      //从刚才打开数据流的流句柄中得到该帧数据，读取到的数据地址存于pImageFrame      hr = m_pNuiSensor->NuiImageStreamGetNextFrame(colorStreamHandle, 0, &pImageFrame_rgb);      if (FAILED(hr))      {        cout<<"Could not get color image"<<endl;        m_pNuiSensor->NuiShutdown();        return -1;      }       INuiFrameTexture *pTexture = pImageFrame_rgb.pFrameTexture;      NUI_LOCKED_RECT lockedRect;       //提取数据帧到LockedRect，它包括两个数据对象：pitch每行字节数，pBits第一个字节地址      //并锁定数据，这样当我们读数据的时候，kinect就不会去修改它        pTexture->LockRect(0, &lockedRect, NULL, 0);      //确认获得的数据是否有效      if (lockedRect.Pitch != 0)      {        //将数据转换为OpenCV的Mat格式        for (int i = 0; i < image_rgb.rows; i++)        {          //第i行的指针          uchar *prt = image_rgb.ptr(i);           //每个字节代表一个颜色信息，直接使用uchar          uchar *pBuffer = (uchar*)(lockedRect.pBits) + i * lockedRect.Pitch;           for (int j = 0; j < image_rgb.cols; j++)          {              prt[3 * j] = pBuffer[4 * j];//内部数据是4个字节，0-1-2是BGR，第4个现在未使用            prt[3 * j + 1] = pBuffer[4 * j + 1];            prt[3 * j + 2] = pBuffer[4 * j + 2];          }        }         imshow("colorImage",image_rgb);        //解除锁定        pTexture->UnlockRect(0);        //释放帧        m_pNuiSensor->NuiImageStreamReleaseFrame(colorStreamHandle, &pImageFrame_rgb );      }      else      {        cout<<"Buffer length of received texture is bogus/r/n"<<endl;      }       BOOL nearMode;      INuiFrameTexture* pColorToDepthTexture;         //深度图像的处理      if (WaitForSingleObject(nextDepthFrameEvent, INFINITE) == 0)      {         hr = m_pNuiSensor->NuiImageStreamGetNextFrame(depthStreamHandle, 0 , &pImageFrame_depth);         if (FAILED(hr))        {          cout<<"Could not get color image"<<endl;          NuiShutdown();          return -1;        }         hr = m_pNuiSensor->NuiImageFrameGetDepthImagePixelFrameTexture(           depthStreamHandle, &pImageFrame_depth, &nearMode, &pColorToDepthTexture);         INuiFrameTexture *pTexture = pImageFrame_depth.pFrameTexture;        NUI_LOCKED_RECT lockedRect;        NUI_LOCKED_RECT ColorToDepthLockRect;          pTexture->LockRect(0, &lockedRect, NULL, 0);        pColorToDepthTexture->LockRect(0,&ColorToDepthLockRect,NULL,0);          //归一化        for (int i = 0; i < image_depth.rows; i++)        {          uchar *prt = image_depth.ptr<uchar>(i);           uchar* pBuffer = (uchar*)(lockedRect.pBits) + i * lockedRect.Pitch;          //这里需要转换，因为每个深度数据是2个字节，应将BYTE转成USHORT          USHORT *pBufferRun = (USHORT*)pBuffer;           for (int j = 0; j < image_depth.cols; j++)          {            //先向，将数据归一化处理，对深度距离在300mm-3500mm范围内的像素，映射到【0—255】内，            //超出范围的，都去做是边缘像素            if (pBufferRun[j] << 3 > MAX_DISTANCE) prt[j] = 255;            else if(pBufferRun[j] << 3 < MIN_DISTANCE) prt[j] = 0;            else prt[j] = (BYTE)(256 * (pBufferRun[j] << 3)/ MAX_DISTANCE);          }        }        imshow("depth", image_depth);           //接下来是对齐部分，将前景抠出来         //存放深度点的参数        NUI_DEPTH_IMAGE_POINT* depthPoints = new NUI_DEPTH_IMAGE_POINT[640 * 480];        if (ColorToDepthLockRect.Pitch != 0)         {           HRESULT hrState = S_OK;                      //一个能在不同空间坐标转变的类（包括：深度，彩色，骨骼）          INuiCoordinateMapper* pMapper;            //设置KINECT实例的空间坐标系          hrState = m_pNuiSensor->NuiGetCoordinateMapper(&pMapper);            if (FAILED(hrState))           {             return hrState;           }            //重要的一步：从颜色空间映射到深度空间。参数说明：          //【参数1】：彩色图像的类型          //【参数2】：彩色图像的分辨率          //【参数3】：深度图像的分辨率          //【参数4】：深度图像的个数          //【参数5】：深度像素点数          //【参数6】：取内存的大小，个数。类型为NUI_DEPTH_IMAGE_PIXEL          //【参数7】：存放映射结果点的参数          hrState = pMapper->MapColorFrameToDepthFrame(NUI_IMAGE_TYPE_COLOR, NUI_IMAGE_RESOLUTION_640x480, NUI_IMAGE_RESOLUTION_640x480,             640 * 480, (NUI_DEPTH_IMAGE_PIXEL*)ColorToDepthLockRect.pBits,640 * 480, depthPoints);            if (FAILED(hrState))           {             return hrState;           }             //显示的图像          Mat show;          show.create(480,640,CV_8UC3);          show = 0;           for (int i = 0; i < image_rgb.rows; i++)          {            for (int j = 0; j < image_rgb.cols; j++)            {              uchar *prt_rgb = image_rgb.ptr(i);              uchar *prt_show = show.ptr(i);              //在内存中偏移量              long index = i * 640 + j;               //从保存了映射坐标的数组中获取点              NUI_DEPTH_IMAGE_POINT depthPointAtIndex = depthPoints[index];                //边界判断              if (depthPointAtIndex.x >= 0 && depthPointAtIndex.x < image_depth.cols &&                depthPointAtIndex.y >=0 && depthPointAtIndex.y < image_depth.rows)              {                //深度判断，在MIN_DISTANCE与MAX_DISTANCE之间的当成前景，显示出来                //这个使用也很重要，当使用真正的深度像素点再在深度图像中获取深度值来判断的时候，会出错                if (depthPointAtIndex.depth >= MIN_DISTANCE && depthPointAtIndex.depth <= MAX_DISTANCE)                {                  prt_show[3 * j]   = prt_rgb[j * 3];                  prt_show[3 * j + 1] = prt_rgb[j * 3 + 1];                  prt_show[3 * j + 2] = prt_rgb[j * 3 + 2];                }              }            }          }          imshow("show", show);        }         delete []depthPoints;                 pTexture->UnlockRect(0);        m_pNuiSensor->NuiImageStreamReleaseFrame(depthStreamHandle, &pImageFrame_depth);      }       else      {        cout<<"Buffer length of received texture is bogus/r/n"<<endl;      }    }     if (cvWaitKey(20) == 27)      break;  }  return 0;}