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~~