#include?“opencv2/opencv.hpp“
#include?
#include?
using?namespace?std;
using?namespace?cv;

class?frameProcessor;
//幀處理基類
class?frameProcessor{
????public:
????????virtual?void?process（Mat?&inputMat?&ouput）=0;
};

//特征跟蹤類，繼承自幀處理基類
class?FeatureTracker?:??public?frameProcessor{
????Mat?gray;??//當前灰度圖
????Mat?gray_prev;??//之前的灰度圖
????vector?points[2];//前后兩幀的特征點
????vector?initial;//初始特征點
????vector?features;//檢測到的特征
????int?max_count;?//要跟蹤特征的最大數目
????double?qlevel;?//特征檢測的指標
????double?minDist;//特征點之間最小容忍距離
????vector?status;?//特征跟蹤狀態
????vector?err;?//跟蹤時的錯誤
public:
????FeatureTracker（）:max_count（500）qlevel（0.01）minDist（10.）{}
????void?process（Mat?&frameMat?&output）{
????????//得到灰度圖
????????cvtColor?（framegrayCV_BGR2GRAY）;
????????frame.copyTo?（output）;
????????//特征點太少了，重新檢測特征點
????????if（addNewPoint（））{
????????????detectFeaturePoint?（）;
????????????//插入檢測到的特征點
????????????points[0].insert?（points[0].end?（）features.begin?（）features.end?（））;
????????????initial.insert?（initial.end?（）features.begin?（）features.end?（））;
????????}
????????//第一幀
????????if（gray_prev.empty?（））{
????????????????gray.copyTo?（gray_prev）;
????????}
????????//根據前后兩幀灰度圖估計前一幀特征點在當前幀的位置
????????//默認窗口是15*15
????????calcOpticalFlowPyrLK?（
????????????????gray_prev//前一幀灰度圖
????????????????gray//當前幀灰度圖
????????????????points[0]//前一幀特征點位置
????????????????points[1]//當前幀特征點位置
????????????????status//特征點被成功跟蹤的標志
????????????????err）;//前一幀特征點點小區域和當前特征點小區域間的差，根據差的大小可刪除那些運動變化劇烈的點
????????int?k?=?0;
????????//去除那些未移動的特征點
????????for（int?i=0;i????????????if（acceptTrackedPoint?（i））{
????????????????initial[k]=initial[i];
????????????????points[1][k++]?=?points[1][i];
????????????}
????????}
????????points[1].resize?（k）;
????????initial.resize?（k）;
????????//標記被跟蹤的特征點
????????handleTrackedPoint?（frameoutput）;
????????//為下一幀跟蹤初始化特征點集和灰度圖像
????????std::swap（points[1]points[0]）;
????????cv::swap（gray_prevgray）;
????}

????void?detectFeaturePoint（）{
????????goodFeaturesToTrack?（gray//圖片
?????????????????????????????????features//輸出特征點
?????????????????????????????????max_count//特征點最大數目
?????????????????????????????????qlevel//質量指標
?????????????????????????????????minDist）;//最小容忍距離
????}
????bool?addNewPoint（）{
????????????//若特征點數目少于10，則決定添加特征點
????????return?points[0].size?（）<=10;
????}

????//若特征點在前后兩幀移動了，則認為該點是目標點，且可被跟蹤
????bool?acceptTrackedPoint（int?i）{
????????return?status[i]&&
????????????????（abs（points[0][i].x-points[1][i].x）+
??????????????????abs（points[0][i].y-points[1][i].y）?>2）;
????}

????//畫特征點
????void??handleTrackedPoint（Mat?&frameMat?&output）{
????????????for（int?i=0;i????????????????//當前特征點到初始位置用直線表示
????????????????line（outputinitial[i]points[1][i]Scalar::all?（0））;
????????????????//當前位置用圈標出
????????????????circle（outputpoints[1][i]3Scalar::all（0）（-1））;
????????????}
????????}
};


class?VideoProcessor{
private:
????VideoCapture?caputure