c++ - 用于运动检测的opencv代码中的错误

Question

我正在寻找实现人类运动跟踪的方法，也在multiple moving object detection中讨论了使用差分分析和lukas kanade光学方法从多个视频帧中提取的内容。

我找到了科学论文，发现我们必须使用连接的组件filtering connected components进行连续运动跟踪，但是我不知道如何进行此过程。我所需要的只是skeletonization轨迹和人体步态运动的坐标。

我正在使用Opencv和C++，但是在我的情况下，opencv中用于对象检测的文档不足。我来自医学背景，需要这是儿科医生项目的一部分。

我找到了这段代码motion detection并试图执行它(尚不知道它是否检测到并跟踪运动)。但是，它返回了这些错误，我感到困惑，因为这些错误是微不足道的，其他注释提到它们能够运行此代码。但是我无法缓解这些错误，也无法理解它们发生的原因。我正在使用OpenCv2.3，以下是错误

无法打开surce文件stdafx.h

警告C4996:'fopen':此函数或变量可能不安全。考虑改用fopen_s。要禁用弃用，请使用_CRT_SECURE_NO_WARNINGS。详细信息请参见在线帮助。

错误C2086:'CvSize imgSize':重新定义

错误C2065:“temp”:未声明的标识符

错误C4430:缺少类型说明符-假定为int。注意:C++不支持default-int

错误C2365:'cvReleaseImage':重新定义;以前的定义是“功能”
1> c:\ opencv2.3 \ opencv \ build \ include \ opencv2 \ core \ core_c.h(87):请参见'cvReleaseImage'

的声明

错误C2065:“差异”:未声明的标识符

错误C4430:缺少类型说明符-假定为int。注意:C++不支持default-int

错误C2365:'cvReleaseImage':重新定义;以前的定义是“功能”
1> c:\ opencv2.3 \ opencv \ build \ include \ opencv2 \ core \ core_c.h(87):请参见'cvReleaseImage'

的声明

错误C2065:“greyImage”:未声明的标识符

错误C4430:缺少类型说明符-假定为int。注意:C++不支持default-int

错误C2365:'cvReleaseImage':重新定义;以前的定义是'function'

\ opencv2.3 \ opencv \ build \ include \ opencv2 \ core \ core_c.h(87):请参见'cvReleaseImage'的声明
错误C2065:“movingAverage”:未声明的标识符
-错误C4430:缺少类型说明符-假定为int。注意:C++不支持default-int
-错误C2365:'cvReleaseImage':重新定义；以前的定义是“功能”
-1> c:\ opencv2.3 \ opencv \ build \ include \ opencv2 \ core \ core_c.h(87):请参见'cvReleaseImage'的声明
-错误C4430:缺少类型说明符-假定为int。注意:C++不支持default-int
-错误C2365:'cvDestroyWindow':重新定义；以前的定义是'function'

c:\ opencv2.3 \ opencv \ build \ include \ opencv2 \ highgui \ highgui_c.h(136):请参见'cvDestroyWindow'声明

错误C2440:“正在初始化”:无法从“const char [10]”转换为“int”
-1>没有可以进行此转换的上下文
-错误C2065:“输入”:未声明的标识符
-错误C4430:缺少类型说明符-假定为int。注意:C++不支持default-int

错误C2365:'cvReleaseCapture':重新定义;以前的定义是“功能”
-1> c:\ opencv2.3 \ opencv \ build \ include \ opencv2 \ highgui \ highgui_c.h(311):请参见'cvReleaseCapture'的声明
-错误C2065:“outputMovie”:未声明的标识符

错误C4430:缺少类型说明符-假定为int。注意:C++不支持default-int
-错误C2365:“cvReleaseVideoWriter”:重新定义；以前的定义是“功能”
-1 c:\ opencv2.3 \ opencv \ build \ include \ opencv2 \ highgui \ highgui_c.h(436):请参见'cvReleaseVideoWriter'的声明
-错误C2059:语法错误:“返回”
========== Build:0成功，1失败，0最新，0跳过==========

CODE

// MotionDetection.cpp : Defines the entry point for the console application.
//


// Contourold.cpp : Defines the entry point for the console application.
//
#include "stdafx.h"

#include "iostream"
#include "stdlib.h"

// OpenCV includes.
#include "cv.h"
#include "highgui.h"
#pragma comment(lib,"cv.lib")
#pragma comment(lib,"cxcore.lib")
#pragma comment(lib,"highgui.lib")

using namespace std;

int main(int argc, char* argv[])
{

//Create a new window.
cvNamedWindow("My Window", CV_WINDOW_AUTOSIZE);

//Create a new movie capture object.
CvCapture *input;

//Assign the movie to capture.
//inputMovie = cvCaptureFromAVI("vinoth.avi");

char *fileName = "E:\\highway.avi";
//char *fileName = "D:\\Profile\\AVI\\cardriving.wmv";
input = cvCaptureFromFile(fileName);
//if (!input)

//cout << "Can't open file" << fileName < ;



//Size of the image.
CvSize imgSize;
IplImage* frame = cvQueryFrame(input);
CvSize imgSize = cvGetSize(frame);

//Images to use in the program.
IplImage* greyImage = cvCreateImage( imgSize, IPL_DEPTH_8U, 1);
IplImage* colourImage;
IplImage* movingAverage = cvCreateImage( imgSize, IPL_DEPTH_32F, 3);
IplImage* difference;
IplImage* temp;
IplImage* motionHistory = cvCreateImage( imgSize, IPL_DEPTH_8U, 3);

//Rectangle to use to put around the people.
CvRect bndRect = cvRect(0,0,0,0);

//Points for the edges of the rectangle.
CvPoint pt1, pt2;

//Create a font object.
CvFont font;


//Create video to output to.
char* outFilename = argc==2 ? argv[1] : "E:\\outputMovie.avi";
CvVideoWriter* outputMovie = cvCreateVideoWriter(outFilename,
CV_FOURCC('F', 'L', 'V', 'I'), 29.97, cvSize(720, 576));

//Capture the movie frame by frame.
int prevX = 0;
int numPeople = 0;

//Buffer to save the number of people when converting the integer
//to a string.
char wow[65];

//The midpoint X position of the rectangle surrounding the moving objects.
int avgX = 0;

//Indicates whether this is the first time in the loop of frames.
bool first = true;

//Indicates the contour which was closest to the left boundary before the object
//entered the region between the buildings.
int closestToLeft = 0;
//Same as above, but for the right.
int closestToRight = 320;

//Keep processing frames...
for(;;)
{
//Get a frame from the input video.
colourImage = cvQueryFrame(input);

//If there are no more frames, jump out of the for.
if( !colourImage )
{
break;
}

//If this is the first time, initialize the images.
if(first)
{
difference = cvCloneImage(colourImage);
temp = cvCloneImage(colourImage);
cvConvertScale(colourImage, movingAverage, 1.0, 0.0);
first = false;
}
//else, make a running average of the motion.
else
{
cvRunningAvg(colourImage, movingAverage, 0.020, NULL);
}

//Convert the scale of the moving average.
cvConvertScale(movingAverage,temp, 1.0, 0.0);

//Minus the current frame from the moving average.
cvAbsDiff(colourImage,temp,difference);

//Convert the image to grayscale.
cvCvtColor(difference,greyImage,CV_RGB2GRAY);

//Convert the image to black and white.
cvThreshold(greyImage, greyImage, 70, 255, CV_THRESH_BINARY);

//Dilate and erode to get people blobs
cvDilate(greyImage, greyImage, 0, 18);
cvErode(greyImage, greyImage, 0, 10);

//Find the contours of the moving images in the frame.
CvMemStorage* storage = cvCreateMemStorage(0);
CvSeq* contour = 0;
cvFindContours( greyImage, storage, &contour, sizeof(CvContour), CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE );

//Process each moving contour in the current frame...
for( ; contour != 0; contour = contour->h_next )
{
//Get a bounding rectangle around the moving object.
bndRect = cvBoundingRect(contour, 0);

pt1.x = bndRect.x;
pt1.y = bndRect.y;
pt2.x = bndRect.x + bndRect.width;
pt2.y = bndRect.y + bndRect.height;

//Get an average X position of the moving contour.
avgX = (pt1.x + pt2.x) / 2;

//If the contour is within the edges of the building...
if(avgX > 90 && avgX < 250)
{
//If the the previous contour was within 2 of the left boundary...
if(closestToLeft >= 88 && closestToLeft <= 90)
{
//If the current X position is greater than the previous...
if(avgX > prevX)
{
//Increase the number of people.
numPeople++;

//Reset the closest object to the left indicator.
closestToLeft = 0;
}
}
//else if the previous contour was within 2 of the right boundary...
else if(closestToRight >= 250 && closestToRight <= 252)
{
//If the current X position is less than the previous...
if(avgX < prevX)
{
//Increase the number of people.
numPeople++;

//Reset the closest object to the right counter.
closestToRight = 320;
}
}

//Draw the bounding rectangle around the moving object.
cvRectangle(colourImage, pt1, pt2, CV_RGB(255,0,0), 1);
}

//If the current object is closer to the left boundary but still not across
//it, then change the closest to the left counter to this value.
if(avgX > closestToLeft && avgX <= 90)
{
closestToLeft = avgX;
}

//If the current object is closer to the right boundary but still not across
//it, then change the closest to the right counter to this value.
if(avgX < closestToRight && avgX >= 250)
{
closestToRight = avgX;
}

//Save the current X value to use as the previous in the next iteration.
prevX = avgX;
}
//Save the current X value to use as the previous in the next iteration.
prevX = avgX;
}


//Write the number of people counted at the top of the output frame.
cvInitFont(&font, CV_FONT_HERSHEY_SIMPLEX, 0.8, 0.8, 0, 2);
cvPutText(colourImage, _itoa(numPeople, wow, 10), cvPoint(60, 200), &font, cvScalar(0, 0, 300));

//Show the frame.
cvShowImage("My Window", colourImage);

//Wait for the user to see it.
cvWaitKey(10);

//Write the frame to the output movie.
cvWriteFrame(outputMovie, colourImage);
}

// Destroy the image, movies, and window.
cvReleaseImage(&temp);
cvReleaseImage(&difference);
cvReleaseImage(&greyImage);
cvReleaseImage(&movingAverage);
cvDestroyWindow("My Window");

cvReleaseCapture(&input);
cvReleaseVideoWriter(&outputMovie);


return 0;

}

请帮助解决错误和问题。

如何进行运动(人类)跟踪，可能通过骨架化方法返回轨迹的坐标。

Answer 1

1.)我想您直接从网站复制了代码(如果我错了，请更正我。)。但是，由于您使用的是OpenCV 2.3，因此大多数API都位于不同的模块中。以下包括您应该拥有的...

#include <opencv/core/core.hpp>
#include <opencv/highgui/highgui.hpp>
#include <opencv/imgproc/imgproc.hpp>

以及相应的库。

2.)要过滤连接的组件，可以使用 cvblob library。我认为OpenCV提供的旧Blob库是使用VC 6构建的，因此可能是所需的 stdafx.h
3.)缓慢浏览代码以获取某些语法和重新声明错误。

编辑代码

#include <iostream>
#include "stdlib.h"


#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>

#include "cv.h"
#include "highgui.h"

using namespace std;
using namespace cv;

int main(int argc, char* argv[])
{
    cvNamedWindow("My Window", CV_WINDOW_AUTOSIZE);
    CvCapture *input;

    //char *fileName = "E:\\highway.avi";
    input = cvCaptureFromCAM(0);

    //input = cvCaptureFromFile(fileName);

    CvSize imgSize;
    IplImage* frame = cvQueryFrame(input);
    imgSize = cvGetSize(frame);

    IplImage* greyImage = cvCreateImage( imgSize, IPL_DEPTH_8U, 1);
    IplImage* colourImage;
    IplImage* movingAverage = cvCreateImage( imgSize, IPL_DEPTH_32F, 3);
    IplImage* difference;
    IplImage* temp;
    IplImage* motionHistory = cvCreateImage( imgSize, IPL_DEPTH_8U, 3);

    CvRect bndRect = cvRect(0,0,0,0);

    CvPoint pt1, pt2;

    CvFont font;


    char* outFilename = argc==2 ? argv[1] : "E:\\outputMovie.avi";
    CvVideoWriter* outputMovie = cvCreateVideoWriter(outFilename,
    CV_FOURCC('F', 'L', 'V', 'I'), 29.97, cvSize(720, 576));

    int prevX = 0;
    int numPeople = 0;

    char wow[65];

    int avgX = 0;

    bool first = true;

    int closestToLeft = 0;
    int closestToRight = 320;

    for(;;)
        {
        colourImage = cvQueryFrame(input);

        if( !colourImage )
            {
            break;
            }
        if(first)
            {
            difference = cvCloneImage(colourImage);
            temp = cvCloneImage(colourImage);
            cvConvertScale(colourImage, movingAverage, 1.0, 0.0);
            first = false;
            }
        else

            {
            cvRunningAvg(colourImage, movingAverage, 0.020, NULL);
            }

        cvConvertScale(movingAverage,temp, 1.0, 0.0);

        cvAbsDiff(colourImage,temp,difference);

        cvCvtColor(difference,greyImage,CV_RGB2GRAY);

        cvThreshold(greyImage, greyImage, 70, 255, CV_THRESH_BINARY);

        cvDilate(greyImage, greyImage, 0, 18);
        cvErode(greyImage, greyImage, 0, 10);

        CvMemStorage* storage = cvCreateMemStorage(0);
        CvSeq* contour = 0;

        cvFindContours( greyImage, storage, &contour, sizeof(CvContour), CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE );


        for( ; contour != 0; contour = contour->h_next )
        {
            bndRect = cvBoundingRect(contour, 0);
            pt1.x = bndRect.x;
            pt1.y = bndRect.y;
            pt2.x = bndRect.x + bndRect.width;
            pt2.y = bndRect.y + bndRect.height;

            avgX = (pt1.x + pt2.x) / 2;

        if(avgX > 90 && avgX < 250)
        {
            if(closestToLeft >= 88 && closestToLeft <= 90)
                {
                if(avgX > prevX)
                    {
                    numPeople++;
                    closestToLeft = 0;
                    }
                }
            else if(closestToRight >= 250 && closestToRight <= 252)
                {
                if(avgX < prevX)
                    {
                    numPeople++;
                    closestToRight = 320;
                    }
                }
            cvRectangle(colourImage, pt1, pt2, CV_RGB(255,0,0), 1);
         }

        if(avgX > closestToLeft && avgX <= 90)
            {
            closestToLeft = avgX;
            }

        if(avgX < closestToRight && avgX >= 250)
            {
            closestToRight = avgX;
            }

        prevX = avgX;
        prevX = avgX;

        }

        cvInitFont(&font, CV_FONT_HERSHEY_SIMPLEX, 0.8, 0.8, 0, 2);
        cvPutText(colourImage, _itoa(numPeople, wow, 10), cvPoint(60, 200), &font, cvScalar(0, 0, 300));
        cvShowImage("My Window", colourImage);

        cvWaitKey(10);
        cvWriteFrame(outputMovie, colourImage);

    }


    cvReleaseImage(&temp);
    cvReleaseImage(&difference);
    cvReleaseImage(&greyImage);
    cvReleaseImage(&movingAverage);
    cvDestroyWindow("My Window");

    cvReleaseCapture(&input);
    cvReleaseVideoWriter(&outputMovie);


return 0;

}

它至少可以正确编译...它有一些运行时错误...我现在没有调试器来跟踪它...尝试它...我也在尝试..