视频前景提取（基于opencv的运动物体检测）

/************************************************************************ * Copyright(c) 2011 Yang Xian * All rights reserved. * * File: extractForeground.cpp * Brief: 提取视频中的前景物体 * Version: 1.0 * Author: Yang Xian * Email: xyang2011@sinano.ac.cn * Date: 2011/11/19 * History: ************************************************************************/ #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; void processing(Mat &frame, Mat &output); string windowResult = "Extracting foreground object"; string windowSource = "Original Video"; Mat gray; // 当前灰度图片 Mat background; // 累积背景 Mat backImage; // 背景图片 Mat foreground; // 前景图片 double learningRate = 0.01; // 控制背景累积学习的速率 int nThreshold = 30; // 前景提取的阈值 int main() { Mat frame; Mat result; // CvCapture* capture = cvCaptureFromCAM( -1 ); // 摄像头读取文件开关 VideoCapture capture("bike.avi"); if(capture.isOpened()/*capture*/) // 摄像头读取文件开关 { while(true) { // frame = cvQueryFrame( capture ); // 摄像头读取文件开关 capture >> frame; if(!frame.empty()) { processing(frame, result); } else { printf(" --(!) No captured frame -- Break!"); break; } int c = waitKey(100); if( (char)c == 27 ) { break; } } } return 0; } void processing(Mat &frame, Mat &output) { cvtColor(frame, gray, CV_BGR2GRAY); // 对于第一帧，初始化背景 if (background.empty()) { gray.convertTo(background, CV_32F); } background.convertTo(backImage, CV_8U); // 计算当前图片和背景的差别 absdiff(backImage, gray, foreground); // 对得到的前景进行阈值选取，去掉伪前景 threshold(foreground, output, nThreshold, 255, THRESH_BINARY_INV); // 实时更新背景 accumulateWeighted(gray, background, learningRate, output); imshow(windowSource, frame); imshow(windowResult, output); }