C++接口:
void calcOpticallFlowPyrLK (InuputArray prevImg, InputArray nextImg, InputArray prevPts, InputOutputArray
nextPts, OutputArray status, OutputArray err, Size winSize = Size(21,21), int maxLevel = 3, TermCriteria
criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01), int flags = 0, double minEigThreshold = 1e-4);
-prevImg: 深度为8位的前一帧图像或金字塔图像。
-nextImg:和prevImg有相同的大小和类型,后一帧图像或金字塔。
-prevPts:计算光流所需要的输入2D点矢量,点坐标必须是单精度浮点数。
-nextPts:输出2D点矢量(也是单精度浮点数坐标),点矢量中包含的是在后一帧图像上计算得到的输入特征新位置。
-status:输出状态矢量(元素是无符号char类型,uchar),如果相应特征的流发现则矢量元素置为1,否则,为0。
-err:输出误差矢量。
-winSize:每个金字塔层搜索窗大小。
-maxLevel:金字塔层的最大数目;如果置0,金字塔不使用(单层);如果置1,金字塔2层,等等以此类推。
-criteria:指定搜索算法收敛迭代的类型
-minEigTheshold:算法计算的光流等式的2x2常规矩阵的最小特征值。
This is a demo of Lukas-Kanade optical flow lkdemo()
#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include
#include
using namespace cv;
using namespace std;
static void help()
{
// print a welcome message, and the OpenCV version
cout << "\nThis is a demo of Lukas-Kanade optical flow lkdemo(),\n"
"Using OpenCV version " << CV_VERSION << endl;
cout << "\nIt uses camera by default, but you can provide a path to video as an argument.\n";
cout << "\nHot keys: \n"
"\tESC - quit the program\n"
"\tr - auto-initialize tracking\n"
"\tc - delete all the points\n"
"\tn - switch the \"night\" mode on/off\n"
"To add/remove a feature point click it\n" << endl;
}
Point2f point;
bool addRemovePt = false;
static void onMouse( int event, int x, int y, int /*flags*/, void* /*param*/ )
{
if( event == CV_EVENT_LBUTTONDOWN )
{
point = Point2f((float)x, (float)y);
addRemovePt = true;
}
}
int main( int argc, char** argv )
{
help();
VideoCapture cap;
TermCriteria termcrit(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 20, 0.03);
Size subPixWinSize(10,10), winSize(31,31);
const int MAX_COUNT = 500;
bool needToInit = false;
bool nightMode = false;
if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))
cap.open(argc == 2 ? argv[1][0] - '0' : 0);
else if( argc == 2 )
cap.open(argv[1]);
if( !cap.isOpened() )
{
cout << "Could not initialize capturing...\n";
return 0;
}
namedWindow( "LK Demo", 1 );
setMouseCallback( "LK Demo", onMouse, 0 );
Mat gray, prevGray, image;
vector points[2];
for(;;)
{
Mat frame;
cap >> frame;
if( frame.empty() )
break;
frame.copyTo(image);
cvtColor(image, gray, COLOR_BGR2GRAY);
if( nightMode )
image = Scalar::all(0);
if( needToInit )
{
// automatic initialization
goodFeaturesToTrack(gray, points[1], MAX_COUNT, 0.01, 10, Mat(), 3, 0, 0.04);
cornerSubPix(gray, points[1], subPixWinSize, Size(-1,-1), termcrit);
addRemovePt = false;
}
else if( !points[0].empty() )
{
vector status;
vector err;
if(prevGray.empty())
gray.copyTo(prevGray);
calcOpticalFlowPyrLK(prevGray, gray, points[0], points[1], status, err, winSize,
3, termcrit, 0, 0.001);
size_t i, k;
for( i = k = 0; i < points[1].size(); i++ )
{
if( addRemovePt )
{
if( norm(point - points[1][i]) <= 5 )
{
addRemovePt = false;
continue;
}
}
if( !status[i] )
continue;
points[1][k++] = points[1][i];
circle( image, points[1][i], 3, Scalar(0,255,0), -1, 8);
}
points[1].resize(k);
}
if( addRemovePt && points[1].size() < (size_t)MAX_COUNT )
{
vector tmp;
tmp.push_back(point);
cornerSubPix( gray, tmp, winSize, cvSize(-1,-1), termcrit);
points[1].push_back(tmp[0]);
addRemovePt = false;
}
needToInit = false;
imshow("LK Demo", image);
char c = (char)waitKey(10);
if( c == 27 )
break;
switch( c )
{
case 'r':
needToInit = true;
break;
case 'c':
points[0].clear();
points[1].clear();
break;
case 'n':
nightMode = !nightMode;
break;
}
std::swap(points[1], points[0]);
cv::swap(prevGray, gray);
}
return 0;
}