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视频前景提取 (III)【Mat版本】

这是(II)中的Mat版本，特别注意一下accumulateWeighted这个函数的用法。

我将官方文档中的函数说明贴出来：

accumulateWeighted

Updates a running average.

C++: void accumulateWeighted(InputArray src, InputOutputArray dst, double alpha, InputArray mask=noArray() )

Python: cv2.accumulateWeighted(src, dst, alpha[, mask]) → None

C: void cvRunningAvg(const CvArr* image, CvArr* acc, double alpha, const CvArr* mask=NULL )

Python: cv.RunningAvg(image, acc, alpha, mask=None) → None

Parameters:	src – Input image as 1- or 3-channel, 8-bit or 32-bit floating point. dst – Accumulator image with the same number of channels as input image, 32-bit or 64-bit floating-point. alpha – Weight of the input image. mask – Optional operation mask.

The function calculates the weighted sum of the input image src and the accumulator dst so that dst becomes a running average of a frame sequence:

That is, alpha regulates the update speed (how fast the accumulator “forgets” about earlier images). The function supports multi-channel images. Each channel is processed independently.

代码：

//opencv2.0风格的视频前景提取

#include "cv.h"
#include "highgui.h"

#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/core/core.hpp>

#include <iostream>
#include <cstdio>

using namespace std;
using namespace cv;


int main()
{
	Mat frame, frame_copy,img1,output,gray,frame_copy_8U;
	double learningRate = 0.01;	// 控制背景累积学习的速率
	char* input_name = "001.avi";

	//从视频读入
	VideoCapture capture(input_name);

	cvNamedWindow( "result", 1 );

	if(capture.isOpened()/*capture*/)	// 摄像头读取文件开关
	{
		//对每一帧做处理

		for(;;)
		{

			//frame = cvQueryFrame( capture );	// 摄像头读取文件开关
			capture >> frame;

			if(!frame.empty())
			{ 
				cvtColor(frame, gray, CV_BGR2GRAY);
				//进行处理
				if (frame_copy.empty())
				{
					//记录第一帧
					gray.convertTo(frame_copy, CV_32F);
				}
				frame_copy.convertTo(frame_copy_8U, CV_8U);

				//做差分
				absdiff(frame_copy_8U, gray, img1);

				// 对得到的前景进行阈值选取，去掉伪前景
				threshold(img1, output, 30, 255, THRESH_BINARY_INV);

				accumulateWeighted(gray, frame_copy,0.01,output);

				imshow("src", frame);
				imshow("result", output);

			}
			else
			{ 
				printf(" --(!) No captured frame -- Break!");
				break;
			}


			//10ms中按任意键进入此if块
			if( cvWaitKey( 10 ) >= 0 )
				break;
		}
	}

	return 0;
}

更好版本(II)：

//opencv2.0风格的视频前景提取

#include "cv.h"
#include "highgui.h"

#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/core/core.hpp>

#include <iostream>
#include <cstdio>

using namespace std;
using namespace cv;


int main()
{
	Mat frame, frame_copy,img1,output,gray,frame_copy_8U;
	double learningRate;	// 控制背景累积学习的速率
	int nThreshold; //二值化阈值
	char* input_name = "001.avi";


	//从视频读入
	VideoCapture capture(input_name);

	cvNamedWindow( "result", 1 );

	if(capture.isOpened()/*capture*/)	// 摄像头读取文件开关
	{
		//对每一帧做处理

		for(;;)
		{

			//frame = cvQueryFrame( capture );	// 摄像头读取文件开关
			capture >> frame;

			if(!frame.empty())
			{ 
				cvtColor(frame, gray, CV_BGR2GRAY);
				//进行处理
				if (frame_copy.empty())
				{
					//记录第一帧
					gray.convertTo(frame_copy, CV_32F);
				}
				frame_copy.convertTo(frame_copy_8U, CV_8U);

				//做差分
				absdiff(frame_copy_8U, gray, img1);

				// 对得到的前景进行阈值选取，去掉伪前景
				nThreshold=30;
				threshold(img1, output, nThreshold, 255, THRESH_BINARY_INV);

				learningRate = 0.01;
				accumulateWeighted(gray, frame_copy,learningRate,output);

				imshow("src", frame);
				imshow("result", output);

			}
			else
			{ 
				printf(" --(!) No captured frame -- Break!");
				break;
			}


			//10ms中按任意键进入此if块
			if( cvWaitKey( 10 ) >= 0 )
				break;
		}
	}

	return 0;
}

最后更新：2017-04-03 05:39:33

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