OpenCV_基於自適應背景更新的運動目標檢測

下面這段代碼利用OpenCV實現了最為簡單的基於自適應背景更新的運動目標檢測算法。

即：
運動前景提取——背景減除
foreground = |frame - background| > threshold
更新背景模型——滑動平均濾波
background = background + (frame - background) * alpha = background * (1 - alpha) + frame * alpha

//運動前景檢測——基於自適應背景更新
//Author: http://blog.csdn.net/icvpr
#include <iostream>
#include <string>

#include <opencv2/opencv.hpp>

int main(int argc, char** argv)
{
std::string videoFileName = "../test.avi";

int threshold = 25 ; // 二值化阈值
float alpha = 0.01; // 更新速度 [0, 1]

cv::VideoCapture capture;
capture.open(videoFileName);
if (!capture.isOpened())
{
std::cout<<"cannot open video"<<std::endl;
return -1;
}

cv::Mat foregroundImg;
cv::Mat foregroundMat;

cv::Mat backgroundImg;
cv::Mat backgroundMat;

cv::Mat frame;
cv::Mat grayImg;
cv::Mat grayMat;

while (capture.read(frame))
{
cv::cvtColor(frame, grayImg, CV_BGR2GRAY);
grayImg.convertTo(grayMat, CV_32FC1);

if (backgroundMat.empty())
{
grayImg.copyTo(backgroundImg);
grayImg.convertTo(backgroundMat, CV_32FC1);
}

// 背景減除
cv::absdiff(grayMat, backgroundMat, foregroundMat);

// 自適應背景更新
cv::addWeighted(backgroundMat, alpha, foregroundMat, 1-alpha, 0, backgroundMat);

// 二值化，獲取前景像素點
cv::threshold(foregroundMat, foregroundMat, threshold, 255, CV_THRESH_BINARY);

// 為了顯示用，將CV_32FC1轉換為CV_8U
cv::convertScaleAbs(foregroundMat, foregroundImg);
cv::convertScaleAbs(backgroundMat, backgroundImg);

cv::imshow("frame", frame);
cv::imshow("foreground", foregroundImg);
cv::imshow("background", backgroundImg);

if (cv::waitKey(25) > 0)
{
break;
}
}

return 0;
}