OpenCV 学习笔记（11）【OpenCV】光流场方法标出前景（运动）和背景（静止）

用光流场方法，标出前景（运动）和背景（静止）。

环境：VS2017 + OpenCV3.4.1

光流场介绍可以参见英文版学习OpenCV3的第17章Tracking

英文原版学习OpenCV3下载链接

https://download.csdn.net/download/iefenghao/11194776

视频测试

步骤

（1）打开视频

（2）转为灰度图

（3）光流检测，标出前景

#include <iostream>

#include "opencv2/opencv.hpp"

using namespace cv;

using namespace std;

#define UNKNOWN_FLOW_THRESH 1e9

void makecolorwheel(vector<Scalar> &colorwheel)

{

	int RY = 15;

	int YG = 6;

	int GC = 4;

	int CB = 11;

	int BM = 13;

	int MR = 6;

	int i;

	for (i = 0; i < RY; i++) colorwheel.push_back(Scalar(255, 255 * i / RY, 0));

	for (i = 0; i < YG; i++) colorwheel.push_back(Scalar(255 - 255 * i / YG, 255, 0));

	for (i = 0; i < GC; i++) colorwheel.push_back(Scalar(0, 255, 255 * i / GC));

	for (i = 0; i < CB; i++) colorwheel.push_back(Scalar(0, 255 - 255 * i / CB, 255));

	for (i = 0; i < BM; i++) colorwheel.push_back(Scalar(255 * i / BM, 0, 255));

	for (i = 0; i < MR; i++) colorwheel.push_back(Scalar(255, 0, 255 - 255 * i / MR));

}

void motionToColor(Mat flow, Mat &color)

{

	if (color.empty())

		color.create(flow.rows, flow.cols, CV_8UC3);

	static vector<Scalar> colorwheel; //Scalar r,g,b

	if (colorwheel.empty())

		makecolorwheel(colorwheel);

	// determine motion range:

	float maxrad = -1;

	// Find max flow to normalize fx and fy

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

	{

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

		{

			Vec2f flow_at_point = flow.at<Vec2f>(i, j);

			float fx = flow_at_point[0];

			float fy = flow_at_point[1];

			if ((fabs(fx) > UNKNOWN_FLOW_THRESH) || (fabs(fy) > UNKNOWN_FLOW_THRESH))

				continue;

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

			maxrad = maxrad > rad ? maxrad : rad;

		}

	}

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

	{

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

		{

			uchar *data = color.data + color.step[0] * i + color.step[1] * j;

			Vec2f flow_at_point = flow.at<Vec2f>(i, j);

			float fx = flow_at_point[0] / maxrad;

			float fy = flow_at_point[1] / maxrad;

			if ((fabs(fx) > UNKNOWN_FLOW_THRESH) || (fabs(fy) > UNKNOWN_FLOW_THRESH))

			{

				data[0] = data[1] = data[2] = 0;

				continue;

			}

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

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

			float fk = (angle + 1.0) / 2.0 * (colorwheel.size() - 1);

			int k0 = (int)fk;

			int k1 = (k0 + 1) % colorwheel.size();

			float f = fk - k0;

			//f = 0; // uncomment to see original color wheel

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

			{

				float col0 = colorwheel[k0][b] / 255.0;

				float col1 = colorwheel[k1][b] / 255.0;

				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

				data[2 - b] = (int)(255.0 * col);

			}

		}

	}

}

int main(int, char**)

{

	VideoCapture cap;

	//cap.open(0);

	cap.open("srcVideo.mp4");

	if (!cap.isOpened())

		return -1;

	Mat prevgray, gray, flow, cflow, frame;

	Mat motion2color;

	for (;;)

	{

		double t = (double)cvGetTickCount();

		cap >> frame;

		cvtColor(frame, gray, CV_BGR2GRAY);

		imshow("src 1210", frame);

		if (prevgray.data)

		{

			calcOpticalFlowFarneback(prevgray, gray, flow, 0.5, 3, 15, 3, 5, 1.2, 0);

			motionToColor(flow, motion2color);

			imshow("dst 1210", motion2color);

		}

		if (waitKey(10) >= 0)

			break;

		std::swap(prevgray, gray);

		t = (double)cvGetTickCount() - t;

		cout << "cost time: " << t / ((double)cvGetTickFrequency()*1000.) << endl;

	}

	return 0;

}