基于kinect1的RGB和depth数据获取并对齐
2018-01-28 20:39
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在vs2010项目中，需要设置属性管理器-属性-VC++目录
包含目录中加入 $(KINECTSDK10_DIR)\inc;
库目录中加入 $(KINECTSDK10_DIR)\lib\x86
KINECTSDK10_DIR为Kinect所安装的路径
在链接器中设置附加依赖项，填入Kinect10.lib
对应的.dll文件复制到C:\Windows\SysWOW64
#include <opencv2\opencv.hpp>
#include<iostream>
#include <Windows.h>
#include "NuiApi.h"
#include<cv.h>
#include <d3d11.h>
using namespace std;
using namespace cv;
//最远距离(mm)
const int MAX_DISTANCE = 3500;
//最近距离(mm)
const int MIN_DISTANCE = 200;
const LONG m_depthWidth = 640;
const LONG m_depthHeight = 480;
const LONG m_colorWidth = 640;
const LONG m_colorHeight = 480;
const LONG cBytesPerPixel = 4;
int main()
{
//彩色图像
Mat image_rgb;
//深度图像
Mat image_depth;
//创建一个MAT
image_rgb.create(480,640,CV_8UC3);
image_depth.create(480,640,CV_8UC1);
//一个KINECT实例指针
INuiSensor* m_pNuiSensor = NULL;
if (m_pNuiSensor != NULL)
{
return 0;
}
//记录当前连接KINECT的数量（为多连接做准备）
int iSensorCount;
//获得当前KINECT的数量
HRESULT hr = NuiGetSensorCount(&iSensorCount);
//按照序列初始化KINETC实例，这里就连接了一个KINECT，所以没有用到循环
hr = NuiCreateSensorByIndex(iSensorCount - 1, &m_pNuiSensor);
//初始化，让其可以接收彩色和深度数据流
hr = m_pNuiSensor->NuiInitialize(NUI_INITIALIZE_FLAG_USES_COLOR | NUI_INITIALIZE_FLAG_USES_DEPTH);
//判断是否出错
if (FAILED(hr))
{
cout<<"NuiInitialize failed"<<endl;
return hr;
}
//彩色图像获取下一帧事件
HANDLE nextColorFrameEvent = CreateEvent(NULL, TRUE, FALSE, NULL);
//彩色图像事件句柄
HANDLE colorStreamHandle = NULL;
//深度图像获取下一帧事件
HANDLE nextDepthFrameEvent = CreateEvent(NULL, TRUE, FALSE, NULL);
//深度图像事件句柄
HANDLE depthStreamHandle = NULL;
//实例打开数据流，这里NUI_IMAGE_TYPE_COLOR表示彩色图像
hr = m_pNuiSensor->NuiImageStreamOpen(NUI_IMAGE_TYPE_COLOR, NUI_IMAGE_RESOLUTION_640x480, 0,2,nextColorFrameEvent,&colorStreamHandle);
if( FAILED( hr ) )//判断是否提取正确
{
cout<<"Could not open color image stream video"<<endl;
m_pNuiSensor->NuiShutdown();
return hr;
}
//实例打开数据流，这里NUI_IMAGE_TYPE_DEPTH表示深度图像
hr = m_pNuiSensor->NuiImageStreamOpen(NUI_IMAGE_TYPE_DEPTH, NUI_IMAGE_RESOLUTION_640x480, 0,2, nextDepthFrameEvent, &depthStreamHandle);
if( FAILED( hr ) )//判断是否提取正确
{
cout<<"Could not open color image stream video"<<endl;
m_pNuiSensor->NuiShutdown();
return hr;
}
cv::namedWindow("depth",1);
moveWindow("depth",300,600);
cv::namedWindow("colorImage",1);
moveWindow("colorImage",0,200);
while (1)
{
NUI_IMAGE_FRAME pImageFrame_rgb;
NUI_IMAGE_FRAME pImageFrame_depth;
//无限等待新的彩色数据，等到后返回
if (WaitForSingleObject(nextColorFrameEvent, 0) == 0)
{
//从刚才打开数据流的流句柄中得到该帧数据，读取到的数据地址存于pImageFrame
hr = m_pNuiSensor->NuiImageStreamGetNextFrame(colorStreamHandle, 0, &pImageFrame_rgb);
if (FAILED(hr))
{
cout<<"Could not get color image"<<endl;
m_pNuiSensor->NuiShutdown();
return -1;
}
INuiFrameTexture *pTexture = pImageFrame_rgb.pFrameTexture;
NUI_LOCKED_RECT lockedRect;
//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
//并锁定数据，这样当我们读数据的时候，kinect就不会去修改它
pTexture->LockRect(0, &lockedRect, NULL, 0);
//确认获得的数据是否有效
if (lockedRect.Pitch != 0)
{
//将数据转换为OpenCV的Mat格式
for (int i = 0; i < image_rgb.rows; i++)
{
//第i行的指针
uchar *prt = image_rgb.ptr(i);
//每个字节代表一个颜色信息，直接使用uchar
uchar *pBuffer = (uchar*)(lockedRect.pBits) + i * lockedRect.Pitch;
for (int j = 0; j < image_rgb.cols; j++)
{
prt[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
prt[3 * j + 1] = pBuffer[4 * j + 1];
prt[3 * j + 2] = pBuffer[4 * j + 2];
}
}
imshow("colorImage",image_rgb);
//解除锁定
pTexture->UnlockRect(0);
//释放帧
m_pNuiSensor->NuiImageStreamReleaseFrame(colorStreamHandle, &pImageFrame_rgb );
}
else
{
cout<<"Buffer length of received texture is bogus\r\n"<<endl;
}
BOOL nearMode;
INuiFrameTexture* pColorToDepthTexture;
//深度图像的处理
if (WaitForSingleObject(nextDepthFrameEvent, INFINITE) == 0)
{
hr = m_pNuiSensor->NuiImageStreamGetNextFrame(depthStreamHandle, 0 , &pImageFrame_depth);
if (FAILED(hr))
{
cout<<"Could not get color image"<<endl;
NuiShutdown();
return -1;
}
hr = m_pNuiSensor->NuiImageFrameGetDepthImagePixelFrameTexture(
depthStreamHandle, &pImageFrame_depth, &nearMode, &pColorToDepthTexture);
INuiFrameTexture *pTexture = pImageFrame_depth.pFrameTexture;
NUI_LOCKED_RECT lockedRect;
NUI_LOCKED_RECT ColorToDepthLockRect;
pTexture->LockRect(0, &lockedRect, NULL, 0);
pColorToDepthTexture->LockRect(0,&ColorToDepthLockRect,NULL,0);
//归一化
for (int i = 0; i < image_depth.rows; i++)
{
uchar *prt = image_depth.ptr<uchar>(i);
uchar* pBuffer = (uchar*)(lockedRect.pBits) + i * lockedRect.Pitch;
//这里需要转换，因为每个深度数据是2个字节，应将BYTE转成USHORT
USHORT *pBufferRun = (USHORT*)pBuffer;
for (int j = 0; j < image_depth.cols; j++)
{
4000
//先向，将数据归一化处理，对深度距离在300mm-3500mm范围内的像素，映射到【0—255】内，
//超出范围的，都去做是边缘像素
if (pBufferRun[j] << 3 > MAX_DISTANCE) prt[j] = 255;
else if(pBufferRun[j] << 3 < MIN_DISTANCE) prt[j] = 0;
else prt[j] = (BYTE)(256 * (pBufferRun[j] << 3)/ MAX_DISTANCE);
}
}
imshow("depth", image_depth);
//接下来是对齐部分，将前景抠出来
//存放深度点的参数
NUI_DEPTH_IMAGE_POINT* depthPoints = new NUI_DEPTH_IMAGE_POINT[640 * 480];
if (ColorToDepthLockRect.Pitch != 0)
{
HRESULT hrState = S_OK;
//一个能在不同空间坐标转变的类（包括：深度，彩色，骨骼）
INuiCoordinateMapper* pMapper;
//设置KINECT实例的空间坐标系
hrState = m_pNuiSensor->NuiGetCoordinateMapper(&pMapper);
if (FAILED(hrState))
{
return hrState;
}
//重要的一步：从颜色空间映射到深度空间。参数说明：
//【参数1】：彩色图像的类型
//【参数2】：彩色图像的分辨率
//【参数3】：深度图像的分辨率
//【参数4】：深度图像的个数
//【参数5】：深度像素点数
//【参数6】：取内存的大小，个数。类型为NUI_DEPTH_IMAGE_PIXEL
//【参数7】：存放映射结果点的参数
hrState = pMapper->MapColorFrameToDepthFrame(NUI_IMAGE_TYPE_COLOR, NUI_IMAGE_RESOLUTION_640x480, NUI_IMAGE_RESOLUTION_640x480,
640 * 480, (NUI_DEPTH_IMAGE_PIXEL*)ColorToDepthLockRect.pBits,640 * 480, depthPoints);
if (FAILED(hrState))
{
return hrState;
}
//显示的图像
Mat show;
show.create(480,640,CV_8UC3);
show = 0;
for (int i = 0; i < image_rgb.rows; i++)
{
for (int j = 0; j < image_rgb.cols; j++)
{
uchar *prt_rgb = image_rgb.ptr(i);
uchar *prt_show = show.ptr(i);
//在内存中偏移量
long index = i * 640 + j;
//从保存了映射坐标的数组中获取点
NUI_DEPTH_IMAGE_POINT depthPointAtIndex = depthPoints[index];
//边界判断
if (depthPointAtIndex.x >= 0 && depthPointAtIndex.x < image_depth.cols &&
depthPointAtIndex.y >=0 && depthPointAtIndex.y < image_depth.rows)
{
//深度判断，在MIN_DISTANCE与MAX_DISTANCE之间的当成前景，显示出来
//这个使用也很重要，当使用真正的深度像素点再在深度图像中获取深度值来判断的时候，会出错
if (depthPointAtIndex.depth >= MIN_DISTANCE && depthPointAtIndex.depth <= MAX_DISTANCE)
{
prt_show[3 * j] = prt_rgb[j * 3];
prt_show[3 * j + 1] = prt_rgb[j * 3 + 1];
prt_show[3 * j + 2] = prt_rgb[j * 3 + 2];
}
}
}
}
imshow("show", show);
}
delete []depthPoints;
pTexture->UnlockRect(0);
m_pNuiSensor->NuiImageStreamReleaseFrame(depthStreamHandle, &pImageFrame_depth);
}
else
{
cout<<"Buffer length of received texture is bogus\r\n"<<endl;
}
}
if (waitKey(20) == 27)
break;
}
return 0;
}
包含目录中加入 $(KINECTSDK10_DIR)\inc;
库目录中加入 $(KINECTSDK10_DIR)\lib\x86
KINECTSDK10_DIR为Kinect所安装的路径
在链接器中设置附加依赖项，填入Kinect10.lib
对应的.dll文件复制到C:\Windows\SysWOW64
#include <opencv2\opencv.hpp>
#include<iostream>
#include <Windows.h>
#include "NuiApi.h"
#include<cv.h>
#include <d3d11.h>
using namespace std;
using namespace cv;
//最远距离(mm)
const int MAX_DISTANCE = 3500;
//最近距离(mm)
const int MIN_DISTANCE = 200;
const LONG m_depthWidth = 640;
const LONG m_depthHeight = 480;
const LONG m_colorWidth = 640;
const LONG m_colorHeight = 480;
const LONG cBytesPerPixel = 4;
int main()
{
//彩色图像
Mat image_rgb;
//深度图像
Mat image_depth;
//创建一个MAT
image_rgb.create(480,640,CV_8UC3);
image_depth.create(480,640,CV_8UC1);
//一个KINECT实例指针
INuiSensor* m_pNuiSensor = NULL;
if (m_pNuiSensor != NULL)
{
return 0;
}
//记录当前连接KINECT的数量（为多连接做准备）
int iSensorCount;
//获得当前KINECT的数量
HRESULT hr = NuiGetSensorCount(&iSensorCount);
//按照序列初始化KINETC实例，这里就连接了一个KINECT，所以没有用到循环
hr = NuiCreateSensorByIndex(iSensorCount - 1, &m_pNuiSensor);
//初始化，让其可以接收彩色和深度数据流
hr = m_pNuiSensor->NuiInitialize(NUI_INITIALIZE_FLAG_USES_COLOR | NUI_INITIALIZE_FLAG_USES_DEPTH);
//判断是否出错
if (FAILED(hr))
{
cout<<"NuiInitialize failed"<<endl;
return hr;
}
//彩色图像获取下一帧事件
HANDLE nextColorFrameEvent = CreateEvent(NULL, TRUE, FALSE, NULL);
//彩色图像事件句柄
HANDLE colorStreamHandle = NULL;
//深度图像获取下一帧事件
HANDLE nextDepthFrameEvent = CreateEvent(NULL, TRUE, FALSE, NULL);
//深度图像事件句柄
HANDLE depthStreamHandle = NULL;
//实例打开数据流，这里NUI_IMAGE_TYPE_COLOR表示彩色图像
hr = m_pNuiSensor->NuiImageStreamOpen(NUI_IMAGE_TYPE_COLOR, NUI_IMAGE_RESOLUTION_640x480, 0,2,nextColorFrameEvent,&colorStreamHandle);
if( FAILED( hr ) )//判断是否提取正确
{
cout<<"Could not open color image stream video"<<endl;
m_pNuiSensor->NuiShutdown();
return hr;
}
//实例打开数据流，这里NUI_IMAGE_TYPE_DEPTH表示深度图像
hr = m_pNuiSensor->NuiImageStreamOpen(NUI_IMAGE_TYPE_DEPTH, NUI_IMAGE_RESOLUTION_640x480, 0,2, nextDepthFrameEvent, &depthStreamHandle);
if( FAILED( hr ) )//判断是否提取正确
{
cout<<"Could not open color image stream video"<<endl;
m_pNuiSensor->NuiShutdown();
return hr;
}
cv::namedWindow("depth",1);
moveWindow("depth",300,600);
cv::namedWindow("colorImage",1);
moveWindow("colorImage",0,200);
while (1)
{
NUI_IMAGE_FRAME pImageFrame_rgb;
NUI_IMAGE_FRAME pImageFrame_depth;
//无限等待新的彩色数据，等到后返回
if (WaitForSingleObject(nextColorFrameEvent, 0) == 0)
{
//从刚才打开数据流的流句柄中得到该帧数据，读取到的数据地址存于pImageFrame
hr = m_pNuiSensor->NuiImageStreamGetNextFrame(colorStreamHandle, 0, &pImageFrame_rgb);
if (FAILED(hr))
{
cout<<"Could not get color image"<<endl;
m_pNuiSensor->NuiShutdown();
return -1;
}
INuiFrameTexture *pTexture = pImageFrame_rgb.pFrameTexture;
NUI_LOCKED_RECT lockedRect;
//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
//并锁定数据，这样当我们读数据的时候，kinect就不会去修改它
pTexture->LockRect(0, &lockedRect, NULL, 0);
//确认获得的数据是否有效
if (lockedRect.Pitch != 0)
{
//将数据转换为OpenCV的Mat格式
for (int i = 0; i < image_rgb.rows; i++)
{
//第i行的指针
uchar *prt = image_rgb.ptr(i);
//每个字节代表一个颜色信息，直接使用uchar
uchar *pBuffer = (uchar*)(lockedRect.pBits) + i * lockedRect.Pitch;
for (int j = 0; j < image_rgb.cols; j++)
{
prt[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
prt[3 * j + 1] = pBuffer[4 * j + 1];
prt[3 * j + 2] = pBuffer[4 * j + 2];
}
}
imshow("colorImage",image_rgb);
//解除锁定
pTexture->UnlockRect(0);
//释放帧
m_pNuiSensor->NuiImageStreamReleaseFrame(colorStreamHandle, &pImageFrame_rgb );
}
else
{
cout<<"Buffer length of received texture is bogus\r\n"<<endl;
}
BOOL nearMode;
INuiFrameTexture* pColorToDepthTexture;
//深度图像的处理
if (WaitForSingleObject(nextDepthFrameEvent, INFINITE) == 0)
{
hr = m_pNuiSensor->NuiImageStreamGetNextFrame(depthStreamHandle, 0 , &pImageFrame_depth);
if (FAILED(hr))
{
cout<<"Could not get color image"<<endl;
NuiShutdown();
return -1;
}
hr = m_pNuiSensor->NuiImageFrameGetDepthImagePixelFrameTexture(
depthStreamHandle, &pImageFrame_depth, &nearMode, &pColorToDepthTexture);
INuiFrameTexture *pTexture = pImageFrame_depth.pFrameTexture;
NUI_LOCKED_RECT lockedRect;
NUI_LOCKED_RECT ColorToDepthLockRect;
pTexture->LockRect(0, &lockedRect, NULL, 0);
pColorToDepthTexture->LockRect(0,&ColorToDepthLockRect,NULL,0);
//归一化
for (int i = 0; i < image_depth.rows; i++)
{
uchar *prt = image_depth.ptr<uchar>(i);
uchar* pBuffer = (uchar*)(lockedRect.pBits) + i * lockedRect.Pitch;
//这里需要转换，因为每个深度数据是2个字节，应将BYTE转成USHORT
USHORT *pBufferRun = (USHORT*)pBuffer;
for (int j = 0; j < image_depth.cols; j++)
{
4000
//先向，将数据归一化处理，对深度距离在300mm-3500mm范围内的像素，映射到【0—255】内，
//超出范围的，都去做是边缘像素
if (pBufferRun[j] << 3 > MAX_DISTANCE) prt[j] = 255;
else if(pBufferRun[j] << 3 < MIN_DISTANCE) prt[j] = 0;
else prt[j] = (BYTE)(256 * (pBufferRun[j] << 3)/ MAX_DISTANCE);
}
}
imshow("depth", image_depth);
//接下来是对齐部分，将前景抠出来
//存放深度点的参数
NUI_DEPTH_IMAGE_POINT* depthPoints = new NUI_DEPTH_IMAGE_POINT[640 * 480];
if (ColorToDepthLockRect.Pitch != 0)
{
HRESULT hrState = S_OK;
//一个能在不同空间坐标转变的类（包括：深度，彩色，骨骼）
INuiCoordinateMapper* pMapper;
//设置KINECT实例的空间坐标系
hrState = m_pNuiSensor->NuiGetCoordinateMapper(&pMapper);
if (FAILED(hrState))
{
return hrState;
}
//重要的一步：从颜色空间映射到深度空间。参数说明：
//【参数1】：彩色图像的类型
//【参数2】：彩色图像的分辨率
//【参数3】：深度图像的分辨率
//【参数4】：深度图像的个数
//【参数5】：深度像素点数
//【参数6】：取内存的大小，个数。类型为NUI_DEPTH_IMAGE_PIXEL
//【参数7】：存放映射结果点的参数
hrState = pMapper->MapColorFrameToDepthFrame(NUI_IMAGE_TYPE_COLOR, NUI_IMAGE_RESOLUTION_640x480, NUI_IMAGE_RESOLUTION_640x480,
640 * 480, (NUI_DEPTH_IMAGE_PIXEL*)ColorToDepthLockRect.pBits,640 * 480, depthPoints);
if (FAILED(hrState))
{
return hrState;
}
//显示的图像
Mat show;
show.create(480,640,CV_8UC3);
show = 0;
for (int i = 0; i < image_rgb.rows; i++)
{
for (int j = 0; j < image_rgb.cols; j++)
{
uchar *prt_rgb = image_rgb.ptr(i);
uchar *prt_show = show.ptr(i);
//在内存中偏移量
long index = i * 640 + j;
//从保存了映射坐标的数组中获取点
NUI_DEPTH_IMAGE_POINT depthPointAtIndex = depthPoints[index];
//边界判断
if (depthPointAtIndex.x >= 0 && depthPointAtIndex.x < image_depth.cols &&
depthPointAtIndex.y >=0 && depthPointAtIndex.y < image_depth.rows)
{
//深度判断，在MIN_DISTANCE与MAX_DISTANCE之间的当成前景，显示出来
//这个使用也很重要，当使用真正的深度像素点再在深度图像中获取深度值来判断的时候，会出错
if (depthPointAtIndex.depth >= MIN_DISTANCE && depthPointAtIndex.depth <= MAX_DISTANCE)
{
prt_show[3 * j] = prt_rgb[j * 3];
prt_show[3 * j + 1] = prt_rgb[j * 3 + 1];
prt_show[3 * j + 2] = prt_rgb[j * 3 + 2];
}
}
}
}
imshow("show", show);
}
delete []depthPoints;
pTexture->UnlockRect(0);
m_pNuiSensor->NuiImageStreamReleaseFrame(depthStreamHandle, &pImageFrame_depth);
}
else
{
cout<<"Buffer length of received texture is bogus\r\n"<<endl;
}
}
if (waitKey(20) == 27)
break;
}
return 0;
}
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