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;
}