kinect学习笔记一

颜色深度图像的显示：初始化、绑定流、提取流。

1、提取颜色数据：

#include 
#include "Windows.h"
#include "MSR_NuiApi.h"
#include "cv.h"
#include "highgui.h"

using namespace std;

int main(int argc,char * argv[])
{
IplImage *colorImage=NULL;
colorImage = cvCreateImage(cvSize(640, 480), 8, 3);

//初始化NUI
HRESULT hr = NuiInitialize(NUI_INITIALIZE_FLAG_USES_COLOR);
if( hr != S_OK )
{
cout<<"NuiInitialize failed"<return hr;
}
//定义事件句柄
HANDLE h1 = CreateEvent( NULL, TRUE, FALSE, NULL );//控制KINECT是否可以开始读取下一帧数据
HANDLE h2 = NULL;//保存数据流的地址，用以提取数据

hr = NuiImageStreamOpen(NUI_IMAGE_TYPE_COLOR,NUI_IMAGE_RESOLUTION_640x480,0,2,h1,&h2);//打开KINECT设备的彩色图信息通道

if( FAILED( hr ) )//判断是否提取正确
{
cout<<"Could not open color image stream video"<NuiShutdown();
return hr;
}

//开始读取彩色图数据
while(1)
{
const NUI_IMAGE_FRAME * pImageFrame = NULL;

if (WaitForSingleObject(h1, INFINITE)==0)//判断是否得到了新的数据
{
NuiImageStreamGetNextFrame(h2, 0, &pImageFrame);//得到该帧数据
NuiImageBuffer *pTexture = pImageFrame->pFrameTexture;
KINECT_LOCKED_RECT LockedRect;
pTexture->LockRect(0, &LockedRect, NULL, 0);//提取数据帧到LockedRect，它包括两个数据对象：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个现在未使用
ptr[3*j+1] = pBuffer[4*j+1];
ptr[3*j+2] = pBuffer[4*j+2];
}
}

cvShowImage("colorImage", colorImage);//显示图像

}
else
{
cout<<"Buffer length of received texture is bogus\r\n"<}
//释放本帧数据，准备迎接下一帧
NuiImageStreamReleaseFrame( h2, pImageFrame );
}

if (cvWaitKey(30) == 27)
break;
}
//关闭NUI链接
NuiShutdown();
return 0;
}

实验结果：

2、提取带有用户ID的深度数据

#include 
#include "Windows.h"
#include "MSR_NuiApi.h"
#include "cv.h"
#include "highgui.h"

using namespace std;

RGBQUAD Nui_ShortToQuad_Depth( USHORT s )//该函数我是调用的SDK自带例子的函数。

{
USHORT RealDepth = (s & 0xfff8) >> 3;//提取距离信息
USHORT Player =  s & 7 ;//提取ID信息

//16bit的信息，其中最低3位是ID（所捕捉到的人的ID），剩下的13位才是信息

BYTE l = 255 - (BYTE)(256*RealDepth/0x0fff);//因为提取的信息时距离信息，这里归一化为0-255。======这里一直不明白为什么是除以0x0fff，希望了解的同志给解释一下。

RGBQUAD q;
q.rgbRed = q.rgbBlue = q.rgbGreen = 0;

switch( Player )
{
case 0:
q.rgbRed = l / 2;
q.rgbBlue = l / 2;
q.rgbGreen = l / 2;
break;
case 1:
q.rgbRed = l;
break;
case 2:
q.rgbGreen = l;
break;
case 3:
q.rgbRed = l / 4;
q.rgbGreen = l;
q.rgbBlue = l;
break;
case 4:
q.rgbRed = l;
q.rgbGreen = l;
q.rgbBlue = l / 4;
break;
case 5:
q.rgbRed = l;
q.rgbGreen = l / 4;
q.rgbBlue = l;
break;
case 6:
q.rgbRed = l / 2;
q.rgbGreen = l / 2;
q.rgbBlue = l;
break;
case 7:
q.rgbRed = 255 - ( l / 2 );
q.rgbGreen = 255 - ( l / 2 );
q.rgbBlue = 255 - ( l / 2 );
}

return q;
}

int main(int argc,char * argv[])
{
IplImage *depthIndexImage=NULL;
depthIndexImage = cvCreateImage(cvSize(320, 240), 8, 3);

//初始化NUI
HRESULT hr = NuiInitialize(NUI_INITIALIZE_FLAG_USES_DEPTH_AND_PLAYER_INDEX );
if( hr != S_OK )
{
cout<<"NuiInitialize failed"<return hr;
}
//打开KINECT设备的彩色图信息通道
HANDLE h1 = CreateEvent( NULL, TRUE, FALSE, NULL );
HANDLE h2 = NULL;

hr = NuiImageStreamOpen(NUI_IMAGE_TYPE_DEPTH_AND_PLAYER_INDEX,NUI_IMAGE_RESOLUTION_320x240,0,2,h1,&h2);//这里根据文档信息，当初始化是NUI_INITIALIZE_FLAG_USES_DEPTH_AND_PLAYER_INDEX时，分辨率只能是320*240或者80*60

if( FAILED( hr ) )
{
cout<<"Could not open color image stream video"<NuiShutdown();
return hr;
}

while(1)
{
const NUI_IMAGE_FRAME * pImageFrame = NULL;

if (WaitForSingleObject(h1, INFINITE)==0)
{
NuiImageStreamGetNextFrame(h2, 0, &pImageFrame);
NuiImageBuffer *pTexture = pImageFrame->pFrameTexture;
KINECT_LOCKED_RECT LockedRect;
pTexture->LockRect(0, &LockedRect, NULL, 0);
if( LockedRect.Pitch != 0 )
{
cvZero(depthIndexImage);
for (int i=0; i<240; i++)
{
uchar* ptr = (uchar*)(depthIndexImage->imageData+i*depthIndexImage->widthStep);
BYTE * pBuffer = (BYTE *)(LockedRect.pBits)+i*LockedRect.Pitch;
USHORT * pBufferRun = (USHORT*) pBuffer;//注意这里需要转换，因为每个数据是2个字节，存储的同上面的颜色信息不一样，这里是2个字节一个信息，不能再用BYTE，转化为USHORT
for (int j=0; j<320; j++)
{
RGBQUAD rgb = Nui_ShortToQuad_Depth(pBufferRun[j]);//调用函数进行转化
ptr[3*j] = rgb.rgbBlue;
ptr[3*j+1] = rgb.rgbGreen;
ptr[3*j+2] = rgb.rgbRed;
}
}

cvShowImage("depthIndexImage", depthIndexImage);
}
else
{
cout<<"Buffer length of received texture is bogus\r\n"<}
//释放本帧数据，准备迎接下一帧
NuiImageStreamReleaseFrame( h2, pImageFrame );
}

if (cvWaitKey(30) == 27)
break;
}
//关闭NUI链接
NuiShutdown();
return 0;
}

实验结果：

3、不带ID的深度数据的提取

#include 
#include "Windows.h"
#include "MSR_NuiApi.h"
#include "cv.h"
#include "highgui.h"

using namespace std;


int main(int argc,char * argv[])
{
IplImage *depthIndexImage=NULL;
depthIndexImage = cvCreateImage(cvSize(320, 240), 8, 1);//这里我们用灰度图来表述深度数据，越远的数据越暗。

//初始化NUI
HRESULT hr = NuiInitialize(NUI_INITIALIZE_FLAG_USES_DEPTH);
if( hr != S_OK )
{
cout<<"NuiInitialize failed"<return hr;
}
//打开KINECT设备的彩色图信息通道
HANDLE h1 = CreateEvent( NULL, TRUE, FALSE, NULL );
HANDLE h2 = NULL;

hr = NuiImageStreamOpen(NUI_IMAGE_TYPE_DEPTH,NUI_IMAGE_RESOLUTION_320x240,0,2,h1,&h2);//这里根据文档信息，当初始化是NUI_INITIALIZE_FLAG_USES_DEPTH_AND_PLAYER_INDEX时，分辨率只能是320*240或者80*60

if( FAILED( hr ) )
{
cout<<"Could not open color image stream video"<NuiShutdown();
return hr;
}

while(1)
{
const NUI_IMAGE_FRAME * pImageFrame = NULL;

if (WaitForSingleObject(h1, INFINITE)==0)
{
NuiImageStreamGetNextFrame(h2, 0, &pImageFrame);
NuiImageBuffer *pTexture = pImageFrame->pFrameTexture;
KINECT_LOCKED_RECT LockedRect;
pTexture->LockRect(0, &LockedRect, NULL, 0);
if( LockedRect.Pitch != 0 )
{
cvZero(depthIndexImage);
for (int i=0; i<240; i++)
{
uchar* ptr = (uchar*)(depthIndexImage->imageData+i*depthIndexImage->widthStep);
BYTE * pBuffer = (BYTE *)(LockedRect.pBits)+i*LockedRect.Pitch;
USHORT * pBufferRun = (USHORT*) pBuffer;//注意这里需要转换，因为每个数据是2个字节，存储的同上面的颜色信息不一样，这里是2个字节一个信息，不能再用BYTE，转化为USHORT
for (int j=0; j<320; j++)
{
ptr[j] = 255 - (BYTE)(256*pBufferRun[j]/0x0fff);//直接将数据归一化处理
}
}

cvShowImage("depthIndexImage", depthIndexImage);
}
else
{
cout<<"Buffer length of received texture is bogus\r\n"<}
//释放本帧数据，准备迎接下一帧
NuiImageStreamReleaseFrame( h2, pImageFrame );
}

if (cvWaitKey(30) == 27)
break;
}
//关闭NUI链接
NuiShutdown();
return 0;
}

实验结果：

4、需要注意的地方

①NUI_INITIALIZE_FLAG_USES_DEPTH_AND_PLAYER_INDEX与NUI_INITIALIZE_FLAG_USES_DEPTH不能同时创建数据流。这个我在试验中证实了。而且单纯的深度图像是左右倒置的。

②文中归一化的地方除以0x0fff的原因是kinect的有效距离是1.2m到3.5m(官方文档)，如果是3.5m那用十六进制表示是0x0DAC，我在实际测试中我的实验室能够测到的最大距离是0x0F87也就是3975mm。估计是官方他们直接使用极限距离0x0FFF来作为除数的。

③文中的cv.h，highgui.h是我使用的opencv中的库，因为对这个比较熟悉。

5、骨骼数据的提取：

#include   
#include "Windows.h"  
#include "MSR_NuiApi.h"  
#include "cv.h"  
#include "highgui.h"  

using namespace std;  

void Nui_DrawSkeleton(NUI_SKELETON_DATA * pSkel,int whichone, IplImage *SkeletonImage)//画出骨骼，第二个参数未使用，想跟踪多人的童鞋可以考虑使用
{
float fx, fy;
CvPoint SkeletonPoint[NUI_SKELETON_POSITION_COUNT];
    for (int i = 0; i     {
        NuiTransformSkeletonToDepthImageF( pSkel->SkeletonPositions[i], &fx, &fy );
SkeletonPoint[i].x = (int)(fx*320+0.5f);
SkeletonPoint[i].y = (int)(fy*240+0.5f);
    }

    for (int i = 0; i     {
        if (pSkel->eSkeletonPositionTrackingState[i] != NUI_SKELETON_POSITION_NOT_TRACKED)//跟踪点一用有三种状态：1没有被跟踪到，2跟踪到，3根据跟踪到的估计到
        {
            cvCircle(SkeletonImage, SkeletonPoint[i], 3, cvScalar(0, 255, 255), -1, 8, 0);
        }
    }
    return;

} 

int main(int argc,char * argv[])  
{  
IplImage *skeletOnImage=NULL;  
skeletOnImage= cvCreateImage(cvSize(320, 240), 8, 3);  

//初始化NUI  
HRESULT hr = NuiInitialize(NUI_INITIALIZE_FLAG_USES_SKELETON );  
if( hr != S_OK )  
{  
cout<<"NuiInitialize failed"<return hr;  
}  
//打开KINECT设备的彩色图信息通道  
HANDLE h1 = CreateEvent( NULL, TRUE, FALSE, NULL );   

hr = NuiSkeletonTrackingEnable( h1, 0 );//打开骨骼跟踪事件
if( FAILED( hr ) )
{
cout <<"NuiSkeletonTrackingEnable fail" <NuiShutdown();
return hr;
}

while(1)  
{  
if(WaitForSingleObject(h1, INFINITE)==0)
{
NUI_SKELETON_FRAME SkeletonFrame;//骨骼帧的定义
bool bFoundSkeleton = false;

if( SUCCEEDED(NuiSkeletonGetNextFrame( 0, &SkeletonFrame )) )//Get the next frame of skeleton data.直接从kinect中提取骨骼帧
{
for( int i = 0 ; i {
if( SkeletonFrame.SkeletonData[i].eTrackingState == NUI_SKELETON_TRACKED )//最多跟踪六个人，检查每个“人”（有可能是空，不是人）是否跟踪到了
{
bFoundSkeleton = true;
}
}
}

if( !bFoundSkeleton )
{
continue;;
}

// smooth out the skeleton data
NuiTransformSmooth(&SkeletonFrame,NULL);//平滑骨骼帧,消除抖动


// draw each skeleton color according to the slot within they are found.
cvZero(skeletonImage);
for( int i = 0 ; i {
// Show skeleton only if it is tracked, and the center-shoulder joint is at least inferred.
                                //断定是否是一个正确骨骼的条件：骨骼被跟踪到并且肩部中心（颈部位置）必须跟踪到。

if( SkeletonFrame.SkeletonData[i].eTrackingState == NUI_SKELETON_TRACKED &&
SkeletonFrame.SkeletonData[i].eSkeletonPositionTrackingState[NUI_SKELETON_POSITION_SHOULDER_CENTER] != NUI_SKELETON_POSITION_NOT_TRACKED)
{
Nui_DrawSkeleton(&SkeletonFrame.SkeletonData[i], i , skeletonImage);
}
}

cvShowImage("skeletonImage", skeletonImage);//显示骨骼图像。
cvWaitKey(30);
}  
}
//关闭NUI链接  
NuiShutdown();  
return 0;  
}

实验结果：没有画出连线，大家如果想继续做可以对那个数组进行处理连线就可以了。