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~~