opencv稀疏光流法-------物体运动跟踪

#include <opencv2/video/video.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/core/core.hpp>
#include <iostream>
#include <cstdio>
using namespace std;
using namespace cv;
//当前帧图片
Mat frame, gray;
//前一帧图片
Mat prev_frame, prev_gray;
//保存特征点
vector<Point2f> features;
//初始化特征点
vector<Point2f> inPoints;
//当前帧和前一帧的点
vector<Point2f> fpts[2];
//特征点跟踪标志位
vector<uchar> status;
//误差和
vector<float> err;
//角点检测
void delectFeature(Mat &inFrame, Mat &ingray);
//画点
void drawFeature(Mat &inFrame);
//运动
void track();
//画运动轨迹
void drawLine();
int main()
{
	VideoCapture capture(0);
	// 摄像头读取文件开关
	if (capture.isOpened())
	{
		while (capture.read(frame)) {
			cvtColor(frame, gray, COLOR_BGR2GRAY);
			if (fpts[0].size() < 40) {
				delectFeature(frame, gray);
				fpts[0].insert(fpts[0].end(), features.begin(), features.end());
				inPoints.insert(inPoints.end(), features.begin(), features.end());

			}
			else {
				putText(frame, "follow", Point(100, 100), 1, 2, Scalar(255, 0, 0), 2, 8);
			}

			if (prev_gray.empty()) {
				gray.copyTo(prev_gray);
			}
			track();
			
			//保存当前帧为前一帧
			gray.copyTo(prev_gray);
			frame.copyTo(prev_frame);
			imshow("1", frame);
			waitKey(27);
		}
	}
	return 0;
}

void delectFeature(Mat &inFrame, Mat &ingray) {
	double maxCorners = 500.0;
	double qualityLevel = 0.01;
	double minDistance = 10.0;
	double blockSize = 3.0;
	double k = 0.04;
	goodFeaturesToTrack(ingray, features, maxCorners, qualityLevel, minDistance, Mat(), blockSize, false, k);
	putText(frame, "get point", Point(100, 100), 1, 2, Scalar(255, 0, 0), 2, 8);

}

void drawFeature(Mat &inFrame) {
	for (size_t t = 0; t < fpts[0].size(); t++) {
		circle(inFrame, fpts[0][t], 2, Scalar(0, 255, 0), 2, 8);
	}
}

void track() {
	calcOpticalFlowPyrLK(prev_gray, gray, fpts[0], fpts[1], status, err);
	int k = 0;
	for (int i = 0; i < fpts[1].size(); i++) {
		double dist = abs(fpts[0][i].x- fpts[1][i].x) + abs(fpts[0][i].y - fpts[1][i].y);
		if (dist > 2 && status[i]) {
			//删除损失的特征点
			inPoints[k] = inPoints[i];
			fpts[1][k++] = fpts[1][i];
		}
	}
	inPoints.resize(k);
	fpts[1].resize(k);
	drawLine();
	swap(fpts[1], fpts[0]);
}

void drawLine() {
	for (size_t t = 0; t < fpts[1].size(); t++) {
		line(frame, inPoints[t], fpts[1][t], Scalar(0, 0, 255), 1, 8, 0);
		circle(frame, fpts[1][t], 2, Scalar(0, 255, 0), 2, 8, 0);
	}
}