注:此教程是对贾志刚老师的opencv课程学习的一个记录,在此表示对贾老师的感谢. 稀疏光流-KLT检测的流程如下所示：
#include <opencv2/opencv.hpp> #include <iostream> using namespace cv; using namespace std; Mat frame, gray; Mat prev_frame, prev_gray; vector<Point2f> features; vector<Point2f> iniPoints; vector<Point2f> fpts[2]; vector<uchar> status; vector<float> errors; void drawFeature(Mat &inFrame); void detectFeatures(Mat &inFrame, Mat &ingray); void klTrackFeature(); void drawTrackLines(); int main(int argc, char** argv) { //VideoCapture capture(0); VideoCapture capture; capture.open("/home/fuhong/code/cpp/opencv_learning/src/object_tracing/video/video_006.mp4"); if (!capture.isOpened()) { printf("could not load video file...\n"); return -1; } namedWindow("camera input", CV_WINDOW_AUTOSIZE); while (capture.read(frame)) { //flip(frame, frame, 1); cvtColor(frame, gray, COLOR_BGR2GRAY); if (fpts[0].size() < 40) { detectFeatures(frame, gray); fpts[0].insert(fpts[0].end(), features.begin(), features.end()); iniPoints.insert(iniPoints.end(), features.begin(), features.end()); } else { printf("tttttttttttttttttttttttttttttttttttttttt...\n"); } if (prev_gray.empty()) { gray.copyTo(prev_gray); } klTrackFeature(); drawFeature(frame); gray.copyTo(prev_gray); frame.copyTo(prev_frame); imshow("camera input", frame); char c = waitKey(50); if (c == 27) { break; } } waitKey(0); return 0; } void detectFeatures(Mat &inFrame, Mat &ingray) { double maxCorners = 5000; double qualitylevel = 0.01; double minDistance = 10; double blockSize = 3; double k = 0.04; goodFeaturesToTrack(ingray, features, maxCorners, qualitylevel, minDistance, Mat(), blockSize, false, k); cout << "detect features : " << features.size() << 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 klTrackFeature() { // KLT calcOpticalFlowPyrLK(prev_gray, gray, fpts[0], fpts[1], status, errors); 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]) { iniPoints[k] = iniPoints[i]; fpts[1][k++] = fpts[1][i]; } } iniPoints.resize(k); fpts[1].resize(k); drawTrackLines(); std::swap(fpts[1], fpts[0]); } void drawTrackLines() { for (size_t t=0; t<fpts[1].size(); t++) { line(frame, iniPoints[t], fpts[1][t], Scalar(0, 255, 0), 1, 8, 0); circle(frame, fpts[1][t], 2, Scalar(0, 0, 255), 2, 8, 0); } }效果如下所示：
