OpenCV 基于Lucas-Kanade光流算法的对象跟踪

视频来源：https://www.youtube.com/watch?v=EvIwL0aSCZY

以下代码用OpenCV实现了视频中基于Lucas-Kanade光流算法【OpenCV中的实现为calcOpticalFlowPyrLK函数】的对象跟踪。为了规避孔径问题，以下代码实现仅对角点【通过goodFeaturesToTrack函数做角点检测】做光流计算。

//
//  main.cpp
//  opencv-learning
//
//  Created by _R on 2019/1/9.
//  Copyright © 2019 _R. All rights reserved.
//

#include 
#include 

using namespace std;
using namespace cv;


int main(int argc, char* argv[])
{
    VideoCapture video = VideoCapture("/Users/_R/Desktop/Flying_disc_freestyle_640x360.mp4");
    if (!video.isOpened()) {
        cout << "could not load video file ..." << endl;
        return -1;
    }
    
    Mat frame, frame_in_gray, prev_frame, prev_frame_in_gray;
    vector initPoints;
    vector feature_points[2];
    vector status_of_feature_points;
    vector errors;
    double count_of_success = 0;
    double distance_between_feature_points = 0.0;
    
    
    
    namedWindow("flying_disc", WINDOW_AUTOSIZE);
    
    while (video.read(frame)) {
        cvtColor(frame, frame_in_gray, COLOR_BGR2GRAY);
        
        if (feature_points[0].empty() || initPoints.size() < 10) {
            
            goodFeaturesToTrack(frame_in_gray, feature_points[0], 1000, 0.01, 10.0);
            initPoints.assign(feature_points[0].begin(), feature_points[0].end());
            
        } else {
            
            goodFeaturesToTrack(frame_in_gray, feature_points[1], 1000, 0.01, 10.0);
            calcOpticalFlowPyrLK(prev_frame_in_gray, frame_in_gray, feature_points[0], feature_points[1], status_of_feature_points, errors);
            
            count_of_success = 0;
            for (size_t t=0; t 2 && status_of_feature_points[t]) {
                    initPoints[count_of_success] = initPoints[t];
                    feature_points[1][count_of_success] = feature_points[1][t];
                    count_of_success++;
                }
                
            }
            initPoints.resize(count_of_success);
            feature_points[1].resize(count_of_success);
            std::swap(feature_points[0], feature_points[1]);
            
            cout << initPoints.size() << " " << feature_points[0].size() << endl;
            
            for (size_t t=0; t

效果展示