基于LK光流的点特征跟踪

#include<iostream>
#include<opencv2/opencv.hpp>
using namespace std;
using namespace cv;

Mat frame, gray;//定义原图像  灰度图像
Mat prev_frame, prev_gray;//表示前一帧的图像帧，前一帧的图像帧的灰度图

vector<Point2f> features;//shi-tomasi角点特征检测数据 存入到features
vector<Point2f> inPoints;//初始化特征数据 用于光流跟踪
vector<Point2f> fpts[2];//保存当前帧和前一帧的特征点数据的位置，表示前一帧fpts[0]  表示当前fpts[1]
vector<uchar> status;//特征点是否成功的标志位
vector<float> errors;//跟踪时区域误差和

void detectFratures(Mat &inFrame, Mat &inGray);
void drawFeature(Mat &inframe);
void lkTrackFeatures();
void drawTrackLines();

int main(){
	//frame = imread("G:/learning/OPENCV/LK/LK/LK.mp4");
	VideoCapture capture;
	capture.open("G:/learning/OPENCV/LK/LK/LK.mp4");
	if (!capture.isOpened()){
		cout << "could not load video file!" << endl;
		return -1;
	}

	namedWindow("Camera output",1);
	while (capture.read(frame)){
		cvtColor(frame, gray, COLOR_BGR2GRAY);

		if (fpts[0].size() < 40){
			detectFratures(frame, gray);
			fpts[0].insert(fpts[0].end(),features.begin(),features.end());
			inPoints.insert(inPoints.end(), features.begin(), features.end());
		}
		else{
			cout << "ttttt--------" << endl;
		}
		detectFratures(frame, gray);
		drawFeature(frame);

		//如果前一帧为空 ，则表示第一帧，将第一帧的gray 拷贝到前一帧
		if (prev_gray.empty()){
			gray.copyTo(prev_gray);
		}

		lkTrackFeatures();//跟踪
		drawFeature(frame);//显示跟踪效果

		//数据更新
		gray.copyTo(prev_gray);
		frame.copyTo(prev_frame);

		imshow("camera input", frame);
		char c = waitKey(50);
		if (c == 27){
			break;
		}
	}

	return 0;
}



void detectFratures(Mat &inFrame, Mat &inGray) {
	double maxCorners = 5000;
	double qualityLevel = 0.01;
	double minDistance = 10;
	double blockSize = 1;
	double k = 0.04;
	goodFeaturesToTrack(inGray, features, maxCorners, qualityLevel, minDistance, Mat(), blockSize, false, k);
	cout << "detectFratures---------" << endl;
}

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

void lkTrackFeatures(){
	//光流法跟踪
	calcOpticalFlowPyrLK(prev_gray, gray, fpts[0], fpts[1], status, errors,Size(21,21),1); 
	int k = 0;
	//特征点过滤
	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]){
			inPoints[k] = inPoints[i];
			fpts[1][k++] = fpts[1][i];
		}
	}
	//保存特征点并绘制跟踪轨迹
	inPoints.resize(k);
	fpts[1].resize(k);
	drawTrackLines();
	std::swap(fpts[1], fpts[0]);

}

//跟踪轨迹绘制
void drawTrackLines(){
	for (size_t t = 0; t < fpts[1].size(); t++){
		line(frame, inPoints[t], fpts[1][t], Scalar(0, 255, 0), 2, 8, 0);
		circle(frame, fpts[1][t], 2, Scalar(0, 0, 255), 2, 8, 0);
	}
}