【Kinect】5th-Kinect深度图像采集和Opencv差帧法运动目标检测

Kinect深度图像采集和Opencv差帧法运动目标检测

#include <windows.h>  #include <iostream>   #include <NuiApi.h>  #include <opencv2/opencv.hpp>using namespace std;using namespace cv;class FrameSubtractionKinect{public:    void ImageOperation(Mat& depthimage, Mat& frame_0, int& num, int& steadyCount);};int main(int argc, char*argv[])//int类型的argc,用来统计程序运行时发送给main函数的命令行参数的个数。                               //char*类型的argv[],为字符串数组，用来存放指向的字符串参数的指针数组，每一个元素指向一个参数。{    Mat image, frame_0;    int num = 1;    int steadyCount = 0;    FrameSubtractionKinect detect;    image.create(240, 320, CV_8UC1);//灰度图表示深度图像    //1.初始化NUI,传入Depth    HRESULT hr = NuiInitialize(NUI_INITIALIZE_FLAG_USES_DEPTH);    if (FAILED(hr))    {        cout << "NuiInitialize failed" << endl;        return hr;    }    //2.定义事件句柄    HANDLE nextColorFrameEvent = CreateEvent(NULL,TRUE,FALSE,NULL);    HANDLE depthStreamHandle = NULL;    //3.打开KINECT设备的深度图信息通道，用depthStreamHandle保存该流的句柄    hr = NuiImageStreamOpen(NUI_IMAGE_TYPE_DEPTH, NUI_IMAGE_RESOLUTION_320x240, 0, 2, nextColorFrameEvent, &depthStreamHandle);    if (FAILED(hr))    {        cout << "Could not open color image stream video" << endl;        NuiShutdown();        return hr;    }    namedWindow("depthImage", CV_WINDOW_AUTOSIZE);    //4.开始读取深度数据    while (1)    {        const NUI_IMAGE_FRAME *pImageFrame = NULL;        //4.1.无限等待新的数据，等到后返回        if (WaitForSingleObject(nextColorFrameEvent, INFINITE) == 0)        {            //4.2.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到pImageFrame            hr = NuiImageStreamGetNextFrame(depthStreamHandle, 0, &pImageFrame);            if (FAILED(hr))            {                cout << "Could not get depth image" << endl;                NuiShutdown();                return -1;            }            INuiFrameTexture *pTexture = pImageFrame->pFrameTexture;            NUI_LOCKED_RECT LockedRect;            //4.3.提取数据帧到LockedRect,包括两个数据对象（pitch每行字节数，pBits第一个字节地址）            pTexture->LockRect(0,&LockedRect,NULL,0);  //锁定数据，读数据时，Kinect就不会去修改            //4.4.确定获得的数据是否有效            if (LockedRect.Pitch != 0)            {                //4.5.将数据转换为OpenCV的Mat格式                //每个深度数据是2个字节，pitch以字节为单位的，地址的偏移是按LockedRect.pBits的地址类型偏移                for (int i = 0; i < image.rows; i++)                {                    uchar *ptr = image.ptr<uchar>(i);     //第i行的指针                    uchar *pBufferRun = (uchar*)(LockedRect.pBits) + i*LockedRect.Pitch;                    USHORT *pBuffer = (USHORT*)pBufferRun;                    for (int j = 0; j < image.cols; j++)                    {                        ptr[j] = 255 - (uchar)(256 * pBuffer[j] / 0x0fff);   //直接将数据归一化                    }                }                imshow("depthImage", image);                detect.ImageOperation(image, frame_0, num, steadyCount);            }            else            {                cout << "Buffer length of received texture is bogus" << endl;            }            //5.处理完解锁            pTexture->UnlockRect(0);            //6.释放本帧数据            NuiImageStreamReleaseFrame(depthStreamHandle,pImageFrame);        }        if (cvWaitKey(20) == 27)            break;    }    //Nui关闭    NuiShutdown();    return 0;}//二差帧法检测运动目标void FrameSubtractionKinect::ImageOperation(Mat& depthimage, Mat& frame_0, int& num, int& steadyCount){    Mat erodeimage;    Mat background, foreground, foreground_BW;    if (num == 1)    {        background = depthimage.clone();        frame_0 = background;    }    else    {        background = frame_0;        frame_0 = depthimage.clone();    }    absdiff(depthimage, background, foreground);    erode(foreground, erodeimage, getStructuringElement(MORPH_RECT, Size(7, 7)));    threshold(erodeimage, foreground_BW, 15, 255, 0);    //imshow("foreground", foreground);    //imshow("ErodeImage", erodeimage);    imshow("foreground_BW", foreground_BW);    num++;    if (num > 2000000000) num = 10;}