运动检测(前景检测)之(一)ViBe
[email protected]
http://blog.csdn.net/zouxy09
因为监控发展的需求,目前前景检测的研究还是很多的,也出现了很多新的方法和思路。个人了解的大概概括为以下一些:
帧差、背景减除(GMM、CodeBook、 SOBS、 SACON、 VIBE、 W4、多帧平均……)、光流(稀疏光流、稠密光流)、运动竞争(Motion Competition)、运动模版(运动历史图像)、时间熵……等等。如果加上他们的改进版,那就是很大的一个家族了。
对于上一些方法的一点简单的对比分析可以参考下:
http://www.cnblogs.com/ronny/archive/2012/04/12/2444053.html
至于哪个最好,看使用环境吧,各有千秋,有一些适用的情况更多,有一些在某些情况下表现更好。这些都需要针对自己的使用情况作测试确定的。呵呵。
推荐一个牛逼的库:http://code.google.com/p/bgslibrary/里面包含了各种背景减除的方法,可以让自己少做很多力气活。
还有王先荣博客上存在不少的分析:
http://www.cnblogs.com/xrwang/archive/2010/02/21/ForegroundDetection.html
下面的博客上转载王先荣的上面几篇,然后加上自己分析了两篇:
http://blog.csdn.net/stellar0
本文主要关注其中的一种背景减除方法:ViBe。stellar0的博客上对ViBe进行了分析,我这里就不再啰嗦了,具体的理论可以参考:
http://www2.ulg.ac.be/telecom/research/vibe/
http://blog.csdn.net/stellar0/article/details/8777283
http://blog.csdn.net/yongshengsilingsa/article/details/6659859
http://www2.ulg.ac.be/telecom/research/vibe/download.html
http://www.cvchina.info/2011/12/25/vibe/
《ViBe: A universal background subtraction algorithm for video sequences》
《ViBe: a powerful technique for background detection and subtraction in video sequences》
ViBe是一种像素级视频背景建模或前景检测的算法,效果优于所熟知的几种算法,对硬件内存占用也少,很简单。我之前根据stellar0的代码(在这里,非常感谢stellar0)改写成一个Mat格式的代码了,现在摆上来和大家交流,具体如下:(在VS2010+OpenCV2.4.2中测试通过)
ViBe.h
- #pragma once
- #include <iostream>
- #include "opencv2/opencv.hpp"
-
- using namespace cv;
- using namespace std;
-
- #define NUM_SAMPLES 20 //每个像素点的样本个数
- #define MIN_MATCHES 2 //#min指数
- #define RADIUS 20 //Sqthere半径
- #define SUBSAMPLE_FACTOR 16 //子采样概率
-
-
- class ViBe_BGS
- {
- public:
- ViBe_BGS(void);
- ~ViBe_BGS(void);
-
- void init(const Mat _image);
- void processFirstFrame(const Mat _image);
- void testAndUpdate(const Mat _image);
- Mat getMask(void){return m_mask;};
-
- private:
- Mat m_samples[NUM_SAMPLES];
- Mat m_foregroundMatchCount;
- Mat m_mask;
- };
ViBe.cpp
- #include <opencv2/opencv.hpp>
- #include <iostream>
- #include "ViBe.h"
-
- using namespace std;
- using namespace cv;
-
- int c_xoff[9] = {-1, 0, 1, -1, 1, -1, 0, 1, 0};
- int c_yoff[9] = {-1, 0, 1, -1, 1, -1, 0, 1, 0};
-
- ViBe_BGS::ViBe_BGS(void)
- {
-
- }
- ViBe_BGS::~ViBe_BGS(void)
- {
-
- }
-
-
- void ViBe_BGS::init(const Mat _image)
- {
- for(int i = 0; i < NUM_SAMPLES; i++)
- {
- m_samples[i] = Mat::zeros(_image.size(), CV_8UC1);
- }
- m_mask = Mat::zeros(_image.size(),CV_8UC1);
- m_foregroundMatchCount = Mat::zeros(_image.size(),CV_8UC1);
- }
-
-
- void ViBe_BGS::processFirstFrame(const Mat _image)
- {
- RNG rng;
- int row, col;
-
- for(int i = 0; i < _image.rows; i++)
- {
- for(int j = 0; j < _image.cols; j++)
- {
- for(int k = 0 ; k < NUM_SAMPLES; k++)
- {
-
- int random = rng.uniform(0, 9);
-
- row = i + c_yoff[random];
- if (row < 0)
- row = 0;
- if (row >= _image.rows)
- row = _image.rows - 1;
-
- col = j + c_xoff[random];
- if (col < 0)
- col = 0;
- if (col >= _image.cols)
- col = _image.cols - 1;
-
- m_samples[k].at<uchar>(i, j) = _image.at<uchar>(row, col);
- }
- }
- }
- }
-
-
- void ViBe_BGS::testAndUpdate(const Mat _image)
- {
- RNG rng;
-
- for(int i = 0; i < _image.rows; i++)
- {
- for(int j = 0; j < _image.cols; j++)
- {
- int matches(0), count(0);
- float dist;
-
- while(matches < MIN_MATCHES && count < NUM_SAMPLES)
- {
- dist = abs(m_samples[count].at<uchar>(i, j) - _image.at<uchar>(i, j));
- if (dist < RADIUS)
- matches++;
- count++;
- }
-
- if (matches >= MIN_MATCHES)
- {
-
- m_foregroundMatchCount.at<uchar>(i, j) = 0;
-
-
- m_mask.at<uchar>(i, j) = 0;
-
-
- int random = rng.uniform(0, SUBSAMPLE_FACTOR);
- if (random == 0)
- {
- random = rng.uniform(0, NUM_SAMPLES);
- m_samples[random].at<uchar>(i, j) = _image.at<uchar>(i, j);
- }
-
-
- random = rng.uniform(0, SUBSAMPLE_FACTOR);
- if (random == 0)
- {
- int row, col;
- random = rng.uniform(0, 9);
- row = i + c_yoff[random];
- if (row < 0)
- row = 0;
- if (row >= _image.rows)
- row = _image.rows - 1;
-
- random = rng.uniform(0, 9);
- col = j + c_xoff[random];
- if (col < 0)
- col = 0;
- if (col >= _image.cols)
- col = _image.cols - 1;
-
- random = rng.uniform(0, NUM_SAMPLES);
- m_samples[random].at<uchar>(row, col) = _image.at<uchar>(i, j);
- }
- }
- else
- {
-
- m_foregroundMatchCount.at<uchar>(i, j)++;
-
-
- m_mask.at<uchar>(i, j) = 255;
-
-
- if (m_foregroundMatchCount.at<uchar>(i, j) > 50)
- {
- int random = rng.uniform(0, SUBSAMPLE_FACTOR);
- if (random == 0)
- {
- random = rng.uniform(0, NUM_SAMPLES);
- m_samples[random].at<uchar>(i, j) = _image.at<uchar>(i, j);
- }
- }
- }
- }
- }
- }
Main.cpp
-
-
-
-
-
-
-
-
- #include "opencv2/opencv.hpp"
- #include "ViBe.h"
- #include <iostream>
- #include <cstdio>
-
- using namespace cv;
- using namespace std;
-
- int main(int argc, char* argv[])
- {
- Mat frame, gray, mask;
- VideoCapture capture;
- capture.open("video.avi");
-
- if (!capture.isOpened())
- {
- cout<<"No camera or video input!\n"<<endl;
- return -1;
- }
-
- ViBe_BGS Vibe_Bgs;
- int count = 0;
-
- while (1)
- {
- count++;
- capture >> frame;
- if (frame.empty())
- break;
- cvtColor(frame, gray, CV_RGB2GRAY);
-
- if (count == 1)
- {
- Vibe_Bgs.init(gray);
- Vibe_Bgs.processFirstFrame(gray);
- cout<<" Training GMM complete!"<<endl;
- }
- else
- {
- Vibe_Bgs.testAndUpdate(gray);
- mask = Vibe_Bgs.getMask();
- morphologyEx(mask, mask, MORPH_OPEN, Mat());
- imshow("mask", mask);
- }
-
- imshow("input", frame);
-
- if ( cvWaitKey(10) == 'q' )
- break;
- }
-
- return 0;
- }