Kinect for Windows V2和V1对照开发___彩色数据获取并用OpenCV2.4.10显示
V1彩色分辨率:640x480
V2彩色分辨率:1920x1080
1,打开彩色图像帧的方式
对于V1: 使用NuiImageStreamOpen方法打开
hr = m_PNuiSensor->NuiImageStreamOpen( NUI_IMAGE_TYPE_COLOR,NUI_IMAGE_RESOLUTION_640x480,0, 2, m_hNextColorFrameEvent,&m_hColorStreamHandle); if( FAILED( hr ) ) { cout<<"Could notopen image stream video"<<endl; return hr; } 这样的方式能够设置分辨率
对于V2:
首先使用 m_pKinectSensor->Open();//打开Kinect if (SUCCEEDED(hr)) { hr =m_pKinectSensor->get_ColorFrameSource(&pColorFrameSource); } 方法get_ColorFrameSource打开彩色帧的源。 然后使用 if (SUCCEEDED(hr)) { hr =pColorFrameSource->OpenReader(&m_pColorFrameReader); } SafeRelease(pColorFrameSource); 方法OpenReader打开彩色帧读取器。
2,更新彩色帧的方式
对于V1:使用NuiImageStreamGetNextFrame方法
NuiImageStreamGetNextFrame(m_hColorStreamHandle,0, &pImageFrame);//得到该帧数据
对于V2:使用AcquireLatestFrame方法
if (!m_pColorFrameReader) { return; } IColorFrame* pColorFrame = NULL; HRESULT hr =m_pColorFrameReader->AcquireLatestFrame(&pColorFrame);
3,数据的处理方式
对于V1:这样的数据获取方式比較明朗看到数据内部结构,
INuiFrameTexture *pTexture =pImageFrame->pFrameTexture; NUI_LOCKED_RECT LockedRect; pTexture->LockRect(0, &LockedRect,NULL, 0);//提取数据帧到LockedRect。它包含两个数据对象:pitch每行字节数。pBits第一个字节地址 if( LockedRect.Pitch != 0 ) { cvZero(colorImage); for (int i=0; i<480; i++) { uchar* ptr =(uchar*)(colorImage->imageData+i*colorImage->widthStep); BYTE * pBuffer =(BYTE*)(LockedRect.pBits)+i*LockedRect.Pitch;//每一个字节代表一个颜色信息。直接使用BYTE for (int j=0; j<640; j++) { ptr[3*j] =pBuffer[4*j];//内部数据是4个字节,0-1-2是BGR,第4个如今未使用 ptr[3*j+1] =pBuffer[4*j+1]; ptr[3*j+2] =pBuffer[4*j+2]; } } //cvWriteFrame(wr_color,colorImage); cvShowImage("colorImage", colorImage);//显示图像
得到的终于形式能够用OpenCV显示。
对于V2: 这样的数据的内部结构是神马样子呢?然后怎样用OpenCV显示出图像数据呢?待查…
RGBQUAD* m_pColorRGBX;//彩色数据存储位置 m_pColorRGBX(NULL)//构造函数初始化 // create heap storage for color pixel data in RGBXformat m_pColorRGBX = new RGBQUAD[cColorWidth *cColorHeight]; //下边就是AcquireLatestFrame之后处理数据 INT64 nTime = 0; IFrameDescription* pFrameDescription =NULL; int nWidth = 0; int nHeight = 0; ColorImageFormat imageFormat = ColorImageFormat_None; UINT nBufferSize = 0; RGBQUAD *pBuffer = NULL; if (SUCCEEDED(hr)) { if (imageFormat == ColorImageFormat_Bgra) { hr =pColorFrame->AccessRawUnderlyingBuffer(&nBufferSize, reinterpret_cast<BYTE**>(&pBuffer)); } else if (m_pColorRGBX) { pBuffer = m_pColorRGBX; nBufferSize = cColorWidth *cColorHeight * sizeof(RGBQUAD); hr = pColorFrame->CopyConvertedFrameDataToArray(nBufferSize,reinterpret_cast<BYTE*>(pBuffer), ColorImageFormat_Bgra); } else { hr = E_FAIL; } } if (SUCCEEDED(hr)) { ProcessColor(nTime, pBuffer,nWidth, nHeight); }
感觉眼下得到的pBuffer就是存储的彩色数据。问题是怎样用OpenCV来显示呢?
4,OpenCV显示
<span style="white-space:pre"> </span>int width = 0; int height = 0; pDescription->get_Width( &width ); // 1920 pDescription->get_Height( &height ); // 1080 unsigned int bufferSize = width * height * 4 * sizeof( unsigned char ); //创建尺寸为height x width 的4通道8位图像 Mat bufferMat( height, width, CV_8UC4 ); Mat colorMat( height / 2, width / 2, CV_8UC4 ); while( 1 ){ // 更新彩色帧 IColorFrame* pColorFrame = nullptr; hResult = pColorReader->AcquireLatestFrame( &pColorFrame ); if( SUCCEEDED( hResult ) ){ hResult = pColorFrame->CopyConvertedFrameDataToArray( bufferSize, reinterpret_cast<BYTE*>( bufferMat.data ), ColorImageFormat::ColorImageFormat_Bgra ); if( SUCCEEDED( hResult ) ){ resize( bufferMat, colorMat, cv::Size(), 0.5, 0.5 ); } } SafeRelease( pColorFrame ); imshow( "Color", colorMat );
当中用到kinect的CopyConvertedFrameDataToArray函数,将图像帧转换为矩阵数据用来显示。
5。V2+VS2012+OpenCV代码
#include <Windows.h> #include <Kinect.h> #include <opencv2/opencv.hpp> using namespace std; using namespace cv; //释放接口须要自定义 template<class Interface> inline void SafeRelease( Interface *& pInterfaceToRelease ) { if( pInterfaceToRelease != NULL ){ pInterfaceToRelease->Release(); pInterfaceToRelease = NULL; } } int main( int argc, char **argv[] ) { //OpenCV中开启CPU的硬件指令优化功能函数 setUseOptimized( true ); // 打开kinect IKinectSensor* pSensor; HRESULT hResult = S_OK; hResult = GetDefaultKinectSensor( &pSensor ); if( FAILED( hResult ) ){ cerr << "Error : GetDefaultKinectSensor" << std::endl; return -1; } hResult = pSensor->Open(); if( FAILED( hResult ) ){ cerr << "Error : IKinectSensor::Open()" << std::endl; return -1; } // 彩色帧源 IColorFrameSource* pColorSource; hResult = pSensor->get_ColorFrameSource( &pColorSource ); if( FAILED( hResult ) ){ cerr << "Error : IKinectSensor::get_ColorFrameSource()" << std::endl; return -1; } //彩色帧读取 IColorFrameReader* pColorReader; hResult = pColorSource->OpenReader( &pColorReader ); if( FAILED( hResult ) ){ cerr << "Error : IColorFrameSource::OpenReader()" << std::endl; return -1; } // Description IFrameDescription* pDescription; hResult = pColorSource->get_FrameDescription( &pDescription ); if( FAILED( hResult ) ){ cerr << "Error : IColorFrameSource::get_FrameDescription()" << std::endl; return -1; } int width = 0; int height = 0; pDescription->get_Width( &width ); // 1920 pDescription->get_Height( &height ); // 1080 unsigned int bufferSize = width * height * 4 * sizeof( unsigned char ); //创建尺寸为height x width 的4通道8位图像 Mat bufferMat( height, width, CV_8UC4 ); Mat colorMat( height / 2, width / 2, CV_8UC4 ); while( 1 ){ // 更新彩色帧 IColorFrame* pColorFrame = nullptr; hResult = pColorReader->AcquireLatestFrame( &pColorFrame ); if( SUCCEEDED( hResult ) ){ hResult = pColorFrame->CopyConvertedFrameDataToArray( bufferSize, reinterpret_cast<BYTE*>( bufferMat.data ), ColorImageFormat::ColorImageFormat_Bgra ); if( SUCCEEDED( hResult ) ){ resize( bufferMat, colorMat, cv::Size(), 0.5, 0.5 ); } } SafeRelease( pColorFrame ); imshow( "Color", colorMat ); if( waitKey( 30 ) == VK_ESCAPE ){ break; } } SafeRelease( pColorSource ); SafeRelease( pColorReader ); SafeRelease( pDescription ); if( pSensor ){ pSensor->Close(); } SafeRelease( pSensor ); return 0; }
分辨率是大大的提高了啊~~