C++实现目标微小运动的检测和跟踪通过meanshift、camshift方法

╰半夏微凉° 2023-01-14 12:59 191阅读 0赞

**meanshift跟踪算法**：

meanshift算法用于视觉跟踪时，将基于前一图像中的对象的颜色直方图在新图像中创建置信度图，并使用均值平移来找到靠近对象旧位置的置信度图的峰值。 置信度图是新图像上的概率密度函数，为新图像的每个像素指定一个概率，该概率是前一图像中的对象中出现的像素颜色的概率。

meanshift跟踪算法步骤：  
① 选择搜索窗口，包括窗口的初始位置、大小、形状（对称或歪斜，矩形或圆心）、类型（均匀、多项式、指数或高斯）；  
② 计算窗口的重心；  
③ 将窗口的中心设置在计算出的重心处；  
④ 返回②步，直到窗口位置不再变化。

**计算色彩投影图（反向投影）**

（1）为了减少光照变化对目标跟踪的影响，首先将图像从RGB颜色空间转换到HSV颜色空间；

（2）对H分量进行直方图统计，直方图代表了不同H分量取值出现的概率，或者说可以据此查找出H分量的大小为x时的概率或像素个数，即，得到颜色概率查找表；

（3）将图像中每个像素的值用其颜色出现的概率进行替换，由此得到颜色概率分布图；

以上三个步骤称之为反向投影，需要提醒的是，颜色概率分布图是一个灰度图像；

**meanshift寻优**

前面提到过meanShift算法是一种非参数概率密度估计方法，它通过不断迭代计算得到最优搜索窗口的位置和大小。

**camshift跟踪算法**

前面提到，camshift其实就是在视频序列的每一帧当中都运用meanShift，并将上一帧的meanshift结果作为下一帧的初始值，如此不断循环迭代，就可以实现目标的跟踪了。

**meanshift:**

#include "core/core.hpp"    
    #include "highgui/highgui.hpp"    
    #include "imgproc/imgproc.hpp"
    #include "video/tracking.hpp"
    #include<iostream>    
    
    using namespace cv;
    using namespace std;
    
    Mat image;
    Mat rectImage;
    Mat imageCopy; //绘制矩形框时用来拷贝原图的图像  
    bool leftButtonDownFlag = false; //左键单击后视频暂停播放的标志位  
    Point originalPoint; //矩形框起点  
    Point processPoint; //矩形框终点  
    
    Mat targetImageHSV;
    int histSize = 200;
    float histR[] = { 0,255 };
    const float *histRange = histR;
    int channels[] = { 0,1 };
    Mat dstHist;
    Rect rect;
    vector<Point> pt; //保存目标轨迹
    void onMouse(int event, int x, int y, int flags, void* ustc); //鼠标回调函数  
    
    int main(int argc, char*argv[])
    {
    	VideoCapture video;
    	image = video.open("D:/testimage/CXK.avi");
    	//VideoCapture video(0);
    	//double fps = video.get(CAP_PROP_FPS); //获取视频帧率  
    	//double pauseTime = 1000 / fps; //两幅画面中间间隔  
    	namedWindow("目标跟踪", 0);
    	setMouseCallback("目标跟踪", onMouse);
    	while (video.read(image))//(true)
    	{
    		int k = waitKey(30);
    		if (!leftButtonDownFlag) //判定鼠标左键没有按下，采取播放视频，否则暂停  
    		{
    			//video >> image;
    			video.read(image);
    
    		}
    
    		if (leftButtonDownFlag) //判定鼠标左键没有按下，采取播放视频，否则暂停  
    		{
    
    			//while (waitKey(0) != 32)
    			waitKey(0);
    
    		}
    
    		//if (!image.data || waitKey(pauseTime) == 27)  //图像为空或Esc键按下退出播放  
    		//{
    		//	break;
    		//}
    
    		if (originalPoint != processPoint && !leftButtonDownFlag)
    		{
    			Mat imageHSV;
    			Mat calcBackImage;
    			cvtColor(image, imageHSV, COLOR_RGB2HSV);
    			calcBackProject(&imageHSV, 2, channels, dstHist, calcBackImage, &histRange);  //反向投影
    			TermCriteria criteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 1000, 0.001);
    			meanShift(calcBackImage, rect, criteria);
    			Mat imageROI = imageHSV(rect);   //更新模板			
    			targetImageHSV = imageHSV(rect);
    			calcHist(&imageROI, 2, channels, Mat(), dstHist, 1, &histSize, &histRange);
    			normalize(dstHist, dstHist, 0.0, 1.0, NORM_MINMAX);   //归一化
    			rectangle(image, rect, Scalar(0, 0, 255), 3);  	//目标绘制	
    			pt.push_back(Point(rect.x + rect.width / 2, rect.y + rect.height / 2));
    			for (int i = 0; i<pt.size() - 1; i++)
    			{
    				line(image, pt[i], pt[i + 1], Scalar(0, 255, 0), 2.5);
    			}
    		}
    		imshow("目标跟踪", image);
    		waitKey(100);
    	}
    	return 0;
    }
    
    
    //*******************************************************************//    
    //鼠标回调函数    
    
    
    
    void onMouse(int event, int x, int y, int flags, void *ustc)
    {
    	if (event == EVENT_LBUTTONDOWN)
    	{
    		leftButtonDownFlag = true; //标志位  
    		originalPoint = Point(x, y);  //设置左键按下点的矩形起点  
    		processPoint = originalPoint;
    	}
    	if (event == EVENT_MOUSEMOVE && leftButtonDownFlag)
    	{
    		imageCopy = image.clone();
    		processPoint = Point(x, y);
    		if (originalPoint != processPoint)
    		{
    			//在复制的图像上绘制矩形  
    			rectangle(imageCopy, originalPoint, processPoint, Scalar(0, 0, 255), 2);
    		}
    		imshow("目标跟踪", imageCopy);
    	}
    	if (event == EVENT_LBUTTONUP)
    	{
    		leftButtonDownFlag = false;
    		rect = Rect(originalPoint, processPoint);
    		rectImage = image(rect); //子图像显示  
    		imshow("Sub Image", rectImage);
    		cvtColor(rectImage, targetImageHSV, COLOR_RGB2HSV);
    		imshow("targetImageHSV", targetImageHSV);
    		calcHist(&targetImageHSV, 2, channels, Mat(), dstHist, 1, &histSize, &histRange, true, false);
    		normalize(dstHist, dstHist, 0, 255, NORM_MINMAX);
    		imshow("dstHist", dstHist);
    	}
    }

![20210420192219852.gif][]

**camshift:**

#include<opencv2/opencv.hpp>
    #include<opencv2/tracking.hpp>
    using namespace cv;
    
    int main()
    {
    	VideoCapture capture;
    	Mat frame;
    	//保存目标轨迹  
    	std::vector<Point> pt;
    	//capture.open(0);
    	frame = capture.open("D:/testimage/video/fish.mp4");
    	if (!capture.isOpened())
    	{
    		printf("can not open camera \n");
    		return -1;
    	}
    	namedWindow("input", WINDOW_AUTOSIZE);
    	namedWindow("output", WINDOW_AUTOSIZE);
    	capture.read(frame);
    	if (frame.empty())
    		return -1;
    	Rect2d first = selectROI("output", frame);
    	Rect selectionROI;
    	selectionROI.width = first.width;
    	selectionROI.height = first.height;
    	selectionROI.x = first.x;
    	selectionROI.y = first.y;
    	printf("x= %d, y=%d, width=%d, height=%d", selectionROI.x, selectionROI.y, selectionROI.width, selectionROI.height);
    
    	Mat mask, hist, backproject;
    	int bins = 120;
    	Mat drawImg = Mat::zeros(300, 300, CV_8UC3);
    
    	while (capture.read(frame))
    	{
    		Mat hsvimage;
    		cvtColor(frame, hsvimage, CV_BGR2HSV);
    		inRange(hsvimage, Scalar(25, 43, 46), Scalar(35, 256, 256), mask);
    		Mat hue = Mat(hsvimage.size(), hsvimage.depth());
    		int channels[] = { 0, 0 };
    		mixChannels(&hsvimage, 1, &hue, 1, channels, 1);
    
    		//ROI直方图计算
    		Mat roi(hue, first);
    		Mat maskroi(mask, first);
    		float hrange[] = { 0, 180 };
    		const float* hranges = hrange;
    		//直方图
    		calcHist(&roi, 1, 0, maskroi, hist, 1, &bins, &hranges);
    		normalize(hist, hist, 0, 255, NORM_MINMAX);
    
    
    		int binw = drawImg.cols / bins;
    		Mat colorIndex = Mat(1, bins, CV_8UC3);
    		for (int i = 0; i < bins; i++)
    		{
    			colorIndex.at<Vec3b>(0, i) = Vec3b(saturate_cast<uchar>(i * 180 / bins), 255, 255);
    		}
    		cvtColor(colorIndex, colorIndex, COLOR_HSV2BGR);
    		for (int i = 0; i < bins; i++)
    		{
    			int val = saturate_cast<int>(hist.at<float>(i)*drawImg.rows / 255);
    			rectangle(drawImg, Point(i*binw, drawImg.rows), Point((i + 1)*binw, drawImg.rows * val), Scalar(colorIndex.at<Vec3b>(0, i)), -1, 8, 0);
    		}
    
    		//计算直方图的反投影
    		calcBackProject(&hue, 1, 0, hist, backproject, &hranges);
    		backproject &= mask;
    		RotatedRect trackBox = CamShift(backproject, selectionROI, TermCriteria((TermCriteria::COUNT | TermCriteria::EPS), 10, 1));
    		Rect rect;
    		rect.x = trackBox.center.x - trackBox.size.width / 2.0;
    		rect.y = trackBox.center.y - trackBox.size.height / 2.0;
    		rect.width = trackBox.size.width;
    		rect.height = trackBox.size.height;
    
    		rectangle(frame, rect, Scalar(255, 255, 0), 3);
    
    		pt.push_back(Point(rect.x + rect.width / 2, rect.y + rect.height / 2));
    		for (int i = 0; i<pt.size() - 1; i++)
    		{
    			line(frame, pt[i], pt[i + 1], Scalar(0, 255, 0), 2.5);
    		}
    		imshow("input", frame);
    		imshow("output", drawImg);
    		waitKey(10);
    	}
    
    	capture.release();
    	return 0;
    }

[meanShift][]

[camshift][]

[https://www.pianshen.com/article/8200812528/][https_www.pianshen.com_article_8200812528]

[20210420192219852.gif]: /images/20221022/603cb0d6b82247229d3beea386101cb5.png
[meanShift]: https://blog.csdn.net/dcrmg/article/details/52694557?utm_medium=distribute.pc_relevant.none-task-blog-2~default~BlogCommendFromMachineLearnPai2~default-13.control&dist_request_id=&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2~default~BlogCommendFromMachineLearnPai2~default-13.control
[camshift]: https://blog.csdn.net/akadiao/article/details/78991095?utm_medium=distribute.pc_relevant.none-task-blog-baidujs_title-1&spm=1001.2101.3001.4242
[https_www.pianshen.com_article_8200812528]: https://www.pianshen.com/article/8200812528/