Kinect for Windows V2和V1對比開發___深度資料擷取

標籤：kinect

V1深度解析度：320x240

V2深度解析度：512x424

1，  開啟深度映像幀的方式

對於V1:

hr = m_PNuiSensor->NuiImageStreamOpen(                                   NUI_IMAGE_TYPE_DEPTH,NUI_IMAGE_RESOLUTION_320x240,0, 2,                                   m_hNextDepthFrameEvent, &m_hDepthStreamHandle);                          if( FAILED( hr ) )                          {                                   cout<<"Could notopen image stream video"<<endl;                                   return hr;                    }這種方式可以設定解析度

對於V2：     

// Initialize the Kinect and get the depth reader        IDepthFrameSource* pDepthFrameSource =NULL;首先使用        hr = m_pKinectSensor->Open();//開啟Kinect         if (SUCCEEDED(hr))        {          hr =m_pKinectSensor->get_DepthFrameSource(&pDepthFrameSource);        }方法get_DepthFrameSource開啟彩色幀的源。然後使用     if (SUCCEEDED(hr))        {            hr =pDepthFrameSource->OpenReader(&m_pDepthFrameReader);        }        SafeRelease(pDepthFrameSource);方法OpenReader開啟彩色幀讀取器。

 

2，   更新深度幀的方式

對於V1：使用NuiImageStreamGetNextFrame方法

NuiImageStreamGetNextFrame(m_hDepthStreamHandle,0, &pImageFrame);;//得到該幀資料</span>

對於V2：使用AcquireLatestFrame方法

   

 if (!m_pDepthFrameReader)    {        return;    }     IDepthFrame* pDepthFrame = NULL;     HRESULT hr =m_pDepthFrameReader->AcquireLatestFrame(&pDepthFrame);

3，  資料的處理方式

對於V1：這種資料擷取方式比較明朗看到資料內部結構，

INuiFrameTexture *pTexture =pImageFrame->pFrameTexture;                          NUI_LOCKED_RECT LockedRect;                          pTexture->LockRect(0, &LockedRect,NULL, 0);                           RGBQUAD q;                           if( LockedRect.Pitch != 0 )                          {                                                                              //BYTE * pBuffer = (BYTE*)(LockedRect.pBits);                                            //INT size =  LockedRect.size;                                            //memcpy_s(m_pDepthBuffer,size, pBuffer, size);                                            //USHORT* pBufferRun =reinterpret_cast<USHORT*>(m_pDepthBuffer);                                   for (int i=0; i<image.rows; i++)                                   {                                   //USHORT* ptr = (USHORT*)depthIndexImage->height;                                            //USHORT* pDepthRow =(USHORT*)(i);                                            //BYTE * pBuffer = (BYTE*)(LockedRect.pBits);                                            uchar *ptr =image.ptr<uchar>(i);  //第i行的指標                                            uchar * pBuffer =(uchar*)(LockedRect.pBits)+i*LockedRect.Pitch;                                            USHORT* pBufferRun =(USHORT*) pBuffer;//注意這裡需要轉換，因為每個資料是2個位元組，儲存的同上面的顏色資訊不一樣，這裡是2個位元組一個資訊，不能再用BYTE，轉化為USHORT                                             for (int j=0; j<image.cols; j++)                                            {                                                                                                       //ptr[j] = 255 -(BYTE)(256*pBufferRun[j]/0x0fff);//直接將資料歸一化處理                                                     //ptr[j]  = pBufferRun[i * 640 + j];                                                     // ptr[j] = 255 -(uchar)(256 * pBufferRun[j]/0x0fff);  //直接將資料歸一化處理                                   int player =pBufferRun[j]&7;                  int data =(pBufferRun[j]&0xfff8) >> 3;                                    uchar imageData = 255-(uchar)(256*data/0x0fff);                  q.rgbBlue = q.rgbGreen =q.rgbRed = 0;                    switch(player)                  {                      case 0:                            q.rgbRed = imageData /2;                            q.rgbBlue = imageData / 2;                            q.rgbGreen = imageData/ 2;                            break;                        case 1:                             q.rgbRed =imageData;                            break;                        case 2:                            q.rgbGreen =imageData;                            break;                        case 3:                            q.rgbRed = imageData /4;                            q.rgbGreen = q.rgbRed*4;  //這裡利用乘的方法，而不用原來的方法可以避免不整除的情況                          q.rgbBlue =q.rgbRed*4;  //可以在後面的getTheContour()中配合使用，避免遺漏一些情況                          break;                        case 4:                            q.rgbBlue = imageData /4;                           q.rgbRed = q.rgbBlue*4;                            q.rgbGreen =q.rgbBlue*4;                            break;                        case 5:                            q.rgbGreen = imageData/ 4;                           q.rgbRed =q.rgbGreen*4;                            q.rgbBlue =q.rgbGreen*4;                            break;                        case 6:                            q.rgbRed = imageData /2;                            q.rgbGreen = imageData/ 2;                             q.rgbBlue =q.rgbGreen*2;                            break;                        case 7:                            q.rgbRed = 255 - (imageData / 2 );                            q.rgbGreen = 255 - (imageData / 2 );                            q.rgbBlue = 255 - (imageData / 2 );                  }                     ptr[3*j] = q.rgbBlue;                  ptr[3*j+1] = q.rgbGreen;                  ptr[3*j+2] = q.rgbRed;                                            }                                   }                                                                     imshow("depthImage",image); //顯示映像得到的最終形式可以用OpenCV顯示。

對於V2：

RGBQUAD*  m_pDepthRGBX;;//深度資料存放區位置m_pDepthRGBX(NULL)//建構函式初始化    // create heap storage for color pixel data in RGBXformat  m_pDepthRGBX = new RGBQUAD[cDepthWidth *cDepthHeight]; //下邊就是AcquireLatestFrame之後處理資料        INT64 nTime = 0;        IFrameDescription* pFrameDescription =NULL;        int nWidth = 0;        int nHeight = 0;        USHORTnDepthMinReliableDistance = 0;        USHORT nDepthMaxDistance =0;        UINT nBufferSize = 0;        UINT16 *pBuffer = NULL;                if (SUCCEEDED(hr))        {            hr =pDepthFrame->AccessUnderlyingBuffer(&nBufferSize, &pBuffer);                   }         if (SUCCEEDED(hr))        {            ProcessDepth(nTime, pBuffer,nWidth, nHeight, nDepthMinReliableDistance, nDepthMaxDistance);        }

感覺目前得到的pBuffer就是儲存的深度資料，問題是如何用OpenCV來顯示呢？   這種資料的內部結構是神馬樣子呢？然後如何用OpenCV顯示出映像資料呢？待查…

Kinect for Windows V2和V1對比開發___深度資料擷取