【流光算法代码实现】Demo

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简介

　　本篇讲解使用opencv提供的流光法算法接口，实现物体跟踪。范例代码为参考修改tvl1_optical_flow.cpp实现。

具体实现

实现代码

#include

#include "opencv2/video/tracking.hpp"

#include "opencv2/highgui/highgui.hpp"

using namespace cv;

using namespace std;

inline bool isFlowCorrect(Point2f u)

{

return !cvIsNaN(u.x) && !cvIsNaN(u.y) && fabs(u.y) < 1e9;

}

static Vec3b computeColor(float fx, float fy)

{

static bool first = true;

// relative lengths of color transitions:

// these are chosen based on perceptual similarity

// (e.g. one can distinguish more shades between red and yellow

// than between yellow and green)

const int RY = 15;

const int YG = 6;

const int GC = 4;

const int CB = 11;

const int BM = 13;

const int MR = 6;

const int NCOLS = RY + YG + GC + CB + BM + MR;

static Vec3i colorWheel[NCOLS];

if (first){

int k = 0;

for (int i = 0; i < RY; ++i, ++k)

colorWheel[k] = Vec3i(255, 255 * i / RY, 0);

for (int i = 0; i < YG; ++i, ++k)

colorWheel[k] = Vec3i(255 - 255 * i / YG, 255, 0);

for (int i = 0; i < GC; ++i, ++k)

colorWheel[k] = Vec3i(0, 255, 255 * i / GC);

for (int i = 0; i < CB; ++i, ++k)

colorWheel[k] = Vec3i(0, 255 - 255 * i / CB, 255);

for (int i = 0; i < BM; ++i, ++k)

colorWheel[k] = Vec3i(255 * i / BM, 0, 255);

for (int i = 0; i < MR; ++i, ++k)

colorWheel[k] = Vec3i(255, 0, 255 - 255 * i / MR);

first = false;

}

const float rad = sqrt(fx * fx + fy * fy);

const float a = atan2(-fy, -fx) / (float)CV_PI;

const float fk = (a + 1.0f) / 2.0f * (NCOLS - 1);

const int k0 = static_cast(fk);

const int k1 = (k0 + 1) % NCOLS;

const float f = fk - k0;

Vec3b pix;

for (int b = 0; b < 3; b++)

{

const float col0 = colorWheel[k0][b] / 255.f;

const float col1 = colorWheel[k1][b] / 255.f;

float col = (1 - f) * col0 + f * col1;

if (rad <= 1)

col = 1 - rad * (1 - col); // increase saturation with radius

else

col *= .75; // out of range

pix[2 - b] = static_cast(255.f * col);

}

return pix;

}

static void drawOpticalFlow(const Mat_& flow, Mat& dst, float maxmotion = -1)

{

dst.create(flow.size(), CV_8UC3);

dst.setTo(Scalar::all(0));

// determine motion range:

float maxrad = maxmotion;

if (maxmotion <= 0)

{

maxrad = 1;

for (int y = 0; y < flow.rows; ++y)

{

for (int x = 0; x < flow.cols; ++x)

{

Point2f u = flow(y, x);

if (!isFlowCorrect(u))

continue;

maxrad = max(maxrad, sqrt(u.x * u.x + u.y * u.y));

}

for (int y = 0; y < flow.rows; ++y)

{

for (int x = 0; x < flow.cols; ++x)

{

Point2f u = flow(y, x);

if (isFlowCorrect(u))

dst.at(y, x) = computeColor(u.x / maxrad, u.y / maxrad);

}

int main(int argc, const char* argv[])

{

Mat frame0;

Mat frame1;

Mat_ flow;

Ptr tvl1 = createOptFlow_DualTVL1();

Mat out;

if (argc < 2){

cerr << "Usage : " << argv[0] << "

return -1;

}

VideoCapture cap;

cap.open(argv[1]);

while(1){

cap >> frame0;

if(frame0.empty()){

cerr<< "video is over!!" << endl;

break;

}

cvtColor(frame0, frame0, CV_BGR2GRAY);

if(!frame1.empty()){

const double start = (double)getTickCount();

tvl1->calc(frame0, frame1, flow);

const double timeSec = (getTickCount() - start) / getTickFrequency();

cout << "calcOpticalFlowDual_TVL1 : " << timeSec << " sec" << endl;

drawOpticalFlow(flow, out);

imshow("out", out);

imshow("src", frame0);

waitKey(10);

}

frame0.copyTo(frame1);

}

waitKey();

return 0;

}

代码讲解

　　1、创建了一个DenseOpticalFlow实例，同时获得打开了需要跟踪处理的video视频到cap中。