光流检测运动物体

来源：互联网发布：java jvm原理一句话编辑：程序博客网时间：2024/05/29 04:21

光流稠密度检测运动物体calcOpticalFlowFarneback（）方法的理解

prev：前一帧图像8位
next：当前帧图像8位
flow：计算出的光流图像
pyr_scale:金字塔层数，取经典参数0.5
levels：初始化金字塔层数
intertions:迭代次数
poly_n:像素邻域的大小
poly_sigma:高斯标准差

#include <iostream>#include <opencv/cv.h>#include <opencv2/highgui/highgui.hpp>#include <opencv2/imgproc/imgproc.hpp>#include <opencv2/imgproc/imgproc.hpp>#include <opencv2/video/tracking.hpp>using namespace std;using namespace cv;/*在经过calcOpticalFlowFarneback处理后，取当前帧与处理后图像对比，得出运动像素的位移和方向变化，并使用颜色画出来*/void DrawOptFlowMap(const Mat& flowmap, Mat& cflowmap){//for循环内y+=5根据自己情况改变，效果不同。    for (int y=0;y<cflowmap.rows;y+=1)    {        for (int x=0;x<cflowmap.cols;x+=1)        {            Point2f fxy = flowmap.at<Point2f>(y,x);            line(cflowmap,Point(x,y),Point(cvRound(x+fxy.x),cvRound(y+fxy.y)),CV_RGB(0,255,0));            circle(cflowmap,Point(x,y),0.5,CV_RGB(255,0,0),1,0);        }    }}int main(){    VideoCapture cap;    cap.open("TestVideo.avi");    if (!cap.isOpened())    {        cout<<"read video wrong";    }    Mat prevgray,gray,flow,cflow,frame;    do     {        cap>>frame;        cvtColor(frame,gray,CV_BGR2GRAY);        if (prevgray.data)        {            calcOpticalFlowFarneback(prevgray,gray,flow,0.5,3,15,3,5,1.2,0);            cvtColor(prevgray, cflow, CV_GRAY2RGB);            DrawOptFlowMap(flow,cflow);            imshow("FLOW",cflow);        }        if (waitKey(100) >= 0)        {            break;        }        swap(prevgray, gray);//获取当前帧    } while (1);    return 0;}

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