如何使用openCV C++獲取kinect視頻圖像和深度圖像？

我是新約的OpenCV（C++）和Kinect。我嘗試從kinect中用C++拍攝視頻圖像。我到處搜索，但沒有找到任何東西。因爲人們使用openNI或OpenKinect製作。我不想使用這個庫。我該怎麼做？？如何使用openCV C++獲取kinect視頻圖像和深度圖像？

謝謝！

來源

2012-12-14 Mehmet Zaim

爲什麼你不想使用這些庫？ –

因爲我爲我的公司製造。他們不想要那些lib。 =（ –

和司機做他們想做的，你要使用的相機？ –

您可以使用Kinect的爲Windows SDK中搶幀，然後將它們轉換爲OpenCV的格式。看到這個代碼例子確實是在Visual Studio（在此thread在微軟論壇上找到），不幸的是我沒有一個Kinect的，現在來測試代碼：

#include "stdafx.h" 

#define COLOR_WIDTH 640  
#define COLOR_HIGHT 480  
#define DEPTH_WIDTH 320  
#define DEPTH_HIGHT 240  
#define SKELETON_WIDTH 640  
#define SKELETON_HIGHT 480  
#define CHANNEL 3 

BYTE buf[DEPTH_WIDTH * DEPTH_HIGHT * CHANNEL]; 

int drawColor(HANDLE h, IplImage* color)  
{ 
    const NUI_IMAGE_FRAME * pImageFrame = NULL; 
    HRESULT hr = NuiImageStreamGetNextFrame(h, 0, &pImageFrame); 
    if (FAILED(hr)) 
    { 
     cout << "Get Image Frame Failed" << endl; 
     return -1; 
    } 
    NuiImageBuffer * pTexture = pImageFrame->pFrameTexture; 
    KINECT_LOCKED_RECT LockedRect; 
    pTexture->LockRect(0, &LockedRect, NULL, 0); 
    if (LockedRect.Pitch != 0) 
    { 
     BYTE * pBuffer = (BYTE*) LockedRect.pBits; 
     cvSetData(color, pBuffer, LockedRect.Pitch); 
    } 
    cvShowImage("color image", color); 
    NuiImageStreamReleaseFrame(h, pImageFrame); 
    return 0; 
} 

int drawDepth(HANDLE h, IplImage* depth) 
{ 
    const NUI_IMAGE_FRAME * pImageFrame = NULL; 
    HRESULT hr = NuiImageStreamGetNextFrame(h, 0, &pImageFrame); 
    if (FAILED(hr)) 
    { 
     cout << "Get Image Frame Failed" << endl; 
     return -1; 
    } 
    // temp1 = depth; 
    NuiImageBuffer * pTexture = pImageFrame->pFrameTexture; 
    KINECT_LOCKED_RECT LockedRect; 
    pTexture->LockRect(0, &LockedRect, NULL, 0); 
    if (LockedRect.Pitch != 0) 
    { 
     USHORT * pBuff = (USHORT*) LockedRect.pBits; 
     for (int i = 0; i < DEPTH_WIDTH * DEPTH_HIGHT; i++) 
     { 
      BYTE index = pBuff[i] & 0x07; 
      USHORT realDepth = (pBuff[i] & 0xFFF8) >> 3; 
      BYTE scale = 255 - (BYTE)(256 * realDepth/0x0fff); 
      buf[CHANNEL * i] = buf[CHANNEL * i + 1] = buf[CHANNEL * i + 2] = 0; 
      switch (index) 
      { 
      case 0: 
       buf[CHANNEL * i] = scale/2; 
       buf[CHANNEL * i + 1] = scale/2; 
       buf[CHANNEL * i + 2] = scale/2; 
       break; 
      case 1: 
       buf[CHANNEL * i] = scale; 
       break; 
      case 2: 
       buf[CHANNEL * i + 1] = scale; 
       break; 
      case 3: 
       buf[CHANNEL * i + 2] = scale; 
       break; 
      case 4: 
       buf[CHANNEL * i] = scale; 
       buf[CHANNEL * i + 1] = scale; 
       break; 
      case 5: 
       buf[CHANNEL * i] = scale; 
       buf[CHANNEL * i + 2] = scale; 
       break; 
      case 6: 
       buf[CHANNEL * i + 1] = scale; 
       buf[CHANNEL * i + 2] = scale; 
       break; 
      case 7: 
       buf[CHANNEL * i] = 255 - scale/2; 
       buf[CHANNEL * i + 1] = 255 - scale/2; 
       buf[CHANNEL * i + 2] = 255 - scale/2; 
       break; 
      } 
     } 
     cvSetData(depth, buf, DEPTH_WIDTH * CHANNEL); 
    } 
    NuiImageStreamReleaseFrame(h, pImageFrame); 
    cvShowImage("depth image", depth); 
    return 0; 
} 

int drawSkeleton(IplImage* skeleton) 
{ 
    NUI_SKELETON_FRAME SkeletonFrame; 
    CvPoint pt[20]; 
    HRESULT hr = NuiSkeletonGetNextFrame(0, &SkeletonFrame); 
    bool bFoundSkeleton = false; 
    for (int i = 0; i < NUI_SKELETON_COUNT; i++) 
    { 
     if (SkeletonFrame.SkeletonData[i].eTrackingState 
       == NUI_SKELETON_TRACKED) 
     { 
      bFoundSkeleton = true; 
     } 
    } 
    // Has skeletons! 
    // 
    if (bFoundSkeleton) 
    { 
     NuiTransformSmooth(&SkeletonFrame, NULL); 
     memset(skeleton->imageData, 0, skeleton->imageSize); 
     for (int i = 0; i < NUI_SKELETON_COUNT; i++) 
     { 
      if (SkeletonFrame.SkeletonData[i].eTrackingState 
        == NUI_SKELETON_TRACKED) 
      { 
       for (int j = 0; j < NUI_SKELETON_POSITION_COUNT; j++) 
       { 
        float fx, fy; 
        NuiTransformSkeletonToDepthImageF(
          SkeletonFrame.SkeletonData[i].SkeletonPositions[j], 
          &fx, &fy); 
        pt[j].x = (int) (fx * SKELETON_WIDTH + 0.5f); 
        pt[j].y = (int) (fy * SKELETON_HIGHT + 0.5f); 
        cvCircle(skeleton, pt[j], 5, CV_RGB(255, 0, 0), -1); 
       } 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_HEAD], 
         pt[NUI_SKELETON_POSITION_SHOULDER_CENTER], 
         CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_SHOULDER_CENTER], 
         pt[NUI_SKELETON_POSITION_SPINE], CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_SPINE], 
         pt[NUI_SKELETON_POSITION_HIP_CENTER], 
         CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_HAND_RIGHT], 
         pt[NUI_SKELETON_POSITION_WRIST_RIGHT], 
         CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_WRIST_RIGHT], 
         pt[NUI_SKELETON_POSITION_ELBOW_RIGHT], 
         CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_ELBOW_RIGHT], 
         pt[NUI_SKELETON_POSITION_SHOULDER_RIGHT], 
         CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_SHOULDER_RIGHT], 
         pt[NUI_SKELETON_POSITION_SHOULDER_CENTER], 
         CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_SHOULDER_CENTER], 
         pt[NUI_SKELETON_POSITION_SHOULDER_LEFT], 
         CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_SHOULDER_LEFT], 
         pt[NUI_SKELETON_POSITION_ELBOW_LEFT], 
         CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_ELBOW_LEFT], 
         pt[NUI_SKELETON_POSITION_WRIST_LEFT], 
         CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_WRIST_LEFT], 
         pt[NUI_SKELETON_POSITION_HAND_LEFT], CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_HIP_CENTER], 
         pt[NUI_SKELETON_POSITION_HIP_RIGHT], CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_HIP_RIGHT], 
         pt[NUI_SKELETON_POSITION_KNEE_RIGHT], 
         CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_KNEE_RIGHT], 
         pt[NUI_SKELETON_POSITION_ANKLE_RIGHT], 
         CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_ANKLE_RIGHT], 
         pt[NUI_SKELETON_POSITION_FOOT_RIGHT], 
         CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_HIP_CENTER], 
         pt[NUI_SKELETON_POSITION_HIP_LEFT], CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_HIP_LEFT], 
         pt[NUI_SKELETON_POSITION_KNEE_LEFT], CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_KNEE_LEFT], 
         pt[NUI_SKELETON_POSITION_ANKLE_LEFT], 
         CV_RGB(0, 255, 0)); 

       cvLine(skeleton, pt[NUI_SKELETON_POSITION_ANKLE_LEFT], 
         pt[NUI_SKELETON_POSITION_FOOT_LEFT], CV_RGB(0, 255, 0)); 
      } 
     } 
    } 
    cvShowImage("skeleton image", skeleton); 
    return 0; 
} 

int main(int argc, char * argv[]) 
{ 
    IplImage* color = cvCreateImageHeader(cvSize(COLOR_WIDTH, COLOR_HIGHT), IPL_DEPTH_8U, 4); 

    IplImage* depth = cvCreateImageHeader(cvSize(DEPTH_WIDTH, DEPTH_HIGHT),IPL_DEPTH_8U, CHANNEL); 

    IplImage* skeleton = cvCreateImage(cvSize(SKELETON_WIDTH, SKELETON_HIGHT),IPL_DEPTH_8U, CHANNEL); 

    cvNamedWindow("color image", CV_WINDOW_AUTOSIZE); 

    cvNamedWindow("depth image", CV_WINDOW_AUTOSIZE); 

    cvNamedWindow("skeleton image", CV_WINDOW_AUTOSIZE); 

    HRESULT hr = NuiInitialize(
      NUI_INITIALIZE_FLAG_USES_DEPTH_AND_PLAYER_INDEX 
      | NUI_INITIALIZE_FLAG_USES_COLOR 
      | NUI_INITIALIZE_FLAG_USES_SKELETON); 

    if (hr != S_OK) 
    { 
     cout << "NuiInitialize failed" << endl; 
     return hr; 
    } 

    HANDLE h1 = CreateEvent(NULL, TRUE, FALSE, NULL); 
    HANDLE h2 = NULL; 
    hr = NuiImageStreamOpen(NUI_IMAGE_TYPE_COLOR, NUI_IMAGE_RESOLUTION_640x480, 
      0, 2, h1, &h2); 
    if (FAILED(hr)) 
    { 
     cout << "Could not open image stream video" << endl; 
     return hr; 
    } 

    HANDLE h3 = CreateEvent(NULL, TRUE, FALSE, NULL); 
    HANDLE h4 = NULL; 
    hr = NuiImageStreamOpen(NUI_IMAGE_TYPE_DEPTH_AND_PLAYER_INDEX, 
      NUI_IMAGE_RESOLUTION_320x240, 0, 2, h3, &h4); 
    if (FAILED(hr)) 
    { 
     cout << "Could not open depth stream video" << endl; 
     return hr; 
    } 

    HANDLE h5 = CreateEvent(NULL, TRUE, FALSE, NULL); 
    hr = NuiSkeletonTrackingEnable(h5, 0); 
    if (FAILED(hr)) 
    { 
     cout << "Could not open skeleton stream video" << endl; 
     return hr; 
    } 

    while (1) 
    { 
     WaitForSingleObject(h1, INFINITE); 
     drawColor(h2, color); 
     WaitForSingleObject(h3, INFINITE); 
     drawDepth(h4, depth); 
     WaitForSingleObject(h5, INFINITE); 
     drawSkeleton(skeleton); 

     //exit 
     int c = cvWaitKey(1); 
     if (c == 27 || c == 'q' || c == 'Q') 
      break; 
    } 

    cvReleaseImageHeader(&depth); 
    cvReleaseImageHeader(&color); 
    cvReleaseImage(&skeleton); 
    cvDestroyWindow("depth image"); 
    cvDestroyWindow("color image"); 
    cvDestroyWindow("skeleton image"); 

    NuiShutdown(); 

    return 0; 

}

來源

2012-12-14 16:43:33

OpenCV的不提供能力連接並處理來自Kinect傳感器的數據;除非您將Kinect視爲常規攝像頭。您將需要使用其中一個API獲取數據並將其發送給OpenCV。從Kinect的獲取數據，你可以使用：

如果你的僱主擁有的一個API的一個問題，那就是有選擇。但是使用OpenCV並不能消除你需要使用其中的一個。

一個quick search on MSDN揭示的主題多線程。我讀過有關的最直接的方法是使用cvSetData導入數據，圖像轉換後：

RGB

IplImage * ovImage = NULL; 
ovImage = cvCreateImage(cvSize(640, 480), 8, 4); 
cvSetData(ovImage, pBuffer, ovImage->widthStep);

深度

ovImage = cvCreateImage(cvSize(640, 480), 8, 1);

我還發現GitHub上的freenomad_vision項目爲OpenCV和OpenGL提供libfreenect支持。如果你不喜歡使用libfreenect，代碼可以很容易地作爲參考，因爲輸入的數據都是相同的，（可能）將被轉換相同。

來源

2012-12-14 17:33:18

如果有人被重定向到這裏尋找一個更簡單的方法來顯示Kinect深度流，我可以通過以下方式對KinectV2執行此操作。。

Mat CDepthMap::getFrame() 
{ 
    IDepthFrame* frame; 
    Mat depthImage; 
    hr = _depth_reader->AcquireLatestFrame(&frame); 
    if (SUCCEEDED(hr)) { 
      const UINT imgSize = sDepthWidth*sDepthHeight; //512*424 
      UINT16 pixelData[imgSize]; 
      hr = frame->CopyFrameDataToArray(imgSize, pixelData); 
      if (SUCCEEDED(hr)) { 
      depthImage = Mat(sDepthHeight,sDepthWidth, CV_8U); 
       for (UINT i = 0; i < imgSize; i++) { 
        UINT16 depth = pixelData[i]; 
        depthImage.at<UINT8>(i) = LOWORD(depth); 
       } 
     } 
     SafeRelease(frame); 
    } 
    return depthImage; 
}

來源

2016-03-16 10:34:54

如何使用openCV C++獲取kinect視頻圖像和深度圖像？

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