理论

背景减法（BS）是用于通过使用静态相机生成前景蒙版（即，包含属于场景中的运动对象的像素的二值图像）的常用且广泛使用的技术。
顾名思义，BS计算前景蒙版，在当前帧和背景模型之间执行减法，包含场景的静态部分，或者更一般地说，考虑到观察场景的特征，可以将所有内容视为背景。
背景建模包括两个主要步骤：

背景初始化;
背景更新。

在第一步中，计算背景的初始模型，而在第二步中更新模型以适应场景中的可能变化。

代码

//opencv
#include "opencv2/imgcodecs.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/videoio.hpp"
#include <opencv2/highgui.hpp>
#include <opencv2/video.hpp>
//C
#include <stdio.h>
//C++
#include <iostream>
#include <sstream>
using namespace cv;
using namespace std;
// Global variables
Mat frame; //current frame
Mat fgMaskMOG2; //fg mask fg mask generated by MOG2 method
Ptr<BackgroundSubtractor> pMOG2; //MOG2 Background subtractor
int keyboard; //input from keyboard
void help();
void processVideo(char* videoFilename);
void processImages(char* firstFrameFilename);
void help()
{
    cout
    << "--------------------------------------------------------------------------" << endl
    << "This program shows how to use background subtraction methods provided by "  << endl
    << " OpenCV. You can process both videos (-vid) and images (-img)."             << endl
                                                                                    << endl
    << "Usage:"                                                                     << endl
    << "./bs {-vid <video filename>|-img <image filename>}"                         << endl
    << "for example: ./bs -vid video.avi"                                           << endl
    << "or: ./bs -img /data/images/1.png"                                           << endl
    << "--------------------------------------------------------------------------" << endl
    << endl;
}
int main(int argc, char* argv[])
{
    //print help information
    help();
    //check for the input parameter correctness
    if(argc != 3) {
        cerr <<"Incorret input list" << endl;
        cerr <<"exiting..." << endl;
        return EXIT_FAILURE;
    }
    //create GUI windows
    namedWindow("Frame");
    namedWindow("FG Mask MOG 2");
    //create Background Subtractor objects
    pMOG2 = createBackgroundSubtractorMOG2(); //MOG2 approach
    if(strcmp(argv[1], "-vid") == 0) {
        //input data coming from a video
        processVideo(argv[2]);
    }
    else if(strcmp(argv[1], "-img") == 0) {
        //input data coming from a sequence of images
        processImages(argv[2]);
    }
    else {
        //error in reading input parameters
        cerr <<"Please, check the input parameters." << endl;
        cerr <<"Exiting..." << endl;
        return EXIT_FAILURE;
    }
    //destroy GUI windows
    destroyAllWindows();
    return EXIT_SUCCESS;
}
void processVideo(char* videoFilename) {
    //create the capture object
    VideoCapture capture(videoFilename);
    if(!capture.isOpened()){
        //error in opening the video input
        cerr << "Unable to open video file: " << videoFilename << endl;
        exit(EXIT_FAILURE);
    }
    //read input data. ESC or 'q' for quitting
    while( (char)keyboard != 'q' && (char)keyboard != 27 ){
        //read the current frame
        if(!capture.read(frame)) {
            cerr << "Unable to read next frame." << endl;
            cerr << "Exiting..." << endl;
            exit(EXIT_FAILURE);
        }
        //update the background model
        pMOG2->apply(frame, fgMaskMOG2);
        //get the frame number and write it on the current frame
        stringstream ss;
        rectangle(frame, cv::Point(10, 2), cv::Point(100,20),
                  cv::Scalar(255,255,255), -1);
        ss << capture.get(CAP_PROP_POS_FRAMES);
        string frameNumberString = ss.str();
        putText(frame, frameNumberString.c_str(), cv::Point(15, 15),
                FONT_HERSHEY_SIMPLEX, 0.5 , cv::Scalar(0,0,0));
        //show the current frame and the fg masks
        imshow("Frame", frame);
        imshow("FG Mask MOG 2", fgMaskMOG2);
        //get the input from the keyboard
        keyboard = waitKey( 30 );
    }
    //delete capture object
    capture.release();
}
void processImages(char* fistFrameFilename) {
    //read the first file of the sequence
    frame = imread(fistFrameFilename);
    if(frame.empty()){
        //error in opening the first image
        cerr << "Unable to open first image frame: " << fistFrameFilename << endl;
        exit(EXIT_FAILURE);
    }
    //current image filename
    string fn(fistFrameFilename);
    //read input data. ESC or 'q' for quitting
    while( (char)keyboard != 'q' && (char)keyboard != 27 ){
        //update the background model
        pMOG2->apply(frame, fgMaskMOG2);
        //get the frame number and write it on the current frame
        size_t index = fn.find_last_of("/");
        if(index == string::npos) {
            index = fn.find_last_of("\\");
        }
        size_t index2 = fn.find_last_of(".");
        string prefix = fn.substr(0,index+1);
        string suffix = fn.substr(index2);
        string frameNumberString = fn.substr(index+1, index2-index-1);
        istringstream iss(frameNumberString);
        int frameNumber = 0;
        iss >> frameNumber;
        rectangle(frame, cv::Point(10, 2), cv::Point(100,20),
                  cv::Scalar(255,255,255), -1);
        putText(frame, frameNumberString.c_str(), cv::Point(15, 15),
                FONT_HERSHEY_SIMPLEX, 0.5 , cv::Scalar(0,0,0));
        //show the current frame and the fg masks
        imshow("Frame", frame);
        imshow("FG Mask MOG 2", fgMaskMOG2);
        //get the input from the keyboard
        keyboard = waitKey( 30 );
        //search for the next image in the sequence
        ostringstream oss;
        oss << (frameNumber + 1);
        string nextFrameNumberString = oss.str();
        string nextFrameFilename = prefix + nextFrameNumberString + suffix;
        //read the next frame
        frame = imread(nextFrameFilename);
        if(frame.empty()){
            //error in opening the next image in the sequence
            cerr << "Unable to open image frame: " << nextFrameFilename << endl;
            exit(EXIT_FAILURE);
        }
        //update the path of the current frame
        fn.assign(nextFrameFilename);
    }
}

解释

首先，分配三个Mat对象来存储当前帧和两个前景掩码，这两个前景掩码通过使用两种不同的BS算法获得。
两个cv :: BackgroundSubtractor对象将用于生成前景蒙版。使用默认参数，但也可以在create函数中声明特定参数。
分析命令行参数。用户可以选择两个选项：

视频文件（通过选择-vid选项）;
图像序列（通过选择-img选项）。

假设您要处理视频文件。读取视频直到到达终点或用户按下按钮“q”或按钮“ESC”。
每个帧都用于计算前景蒙版和更新背景。如果要更改用于更新背景模型的学习速率，可以通过将第三个参数传递给“apply”方法来设置特定的学习速率。
当前帧编号可以从cv :: VideoCapture对象中提取并标记在当前帧的左上角。白色矩形用于突出显示黑色框架编号。
我们准备显示当前的输入框架和结果。
可以使用一系列图像作为输入来执行上面列出的相同操作。调用processImage函数，而不是使用cv :: VideoCapture对象，在为下一帧读取的正确路径个别化之后，使用cv :: imread读取图像。

效果

给定以下输入参数：
程序的输出如下所示：
The video file Video_001.avi is part of the Background Models Challenge (BMC) data set and it can be downloaded from the following link Video_001 (about 32 MB).
如果要处理一系列图像，则必须选择“-img”选项：
程序的输出如下所示：
为了保存输出图像，我们可以使用cv :: imwrite。添加以下代码可以保存前景蒙版。

Opencv视频分析---使用背景减法方法

理论

代码

解释

效果

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