OpenCV_基于自适应背景更新的运动目标检测

转自http://blog.csdn.net/icvpr/article/details/8487271

下面这段代码利用OpenCV实现了最为简单的基于自适应背景更新的运动目标检测算法。

即：

运动前景提取——背景减除

foreground = |frame - background| > threshold 

更新背景模型——滑动平均滤波

background = background + (frame - background) *  alpha  = background * (1 - alpha) + frame * alpha 

 //运动前景检测——基于自适应背景更新
 //Author: www.icvpr.com
 //Blog:   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);
         }

         // 背景减除
         cv::absdiff(grayMat, backgroundMat, foregroundMat);

         // 自适应背景更新
         cv::addWeighted(backgroundMat, alpha, foregroundMat, 1-alpha, 0, backgroundMat);

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


         // 为了显示用，将CV_32FC1转换为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;
 }