算法集合:https://code.google.com/p/bgslibrary/

测试:AdaptiveBackgroundLearning算法

#include <iostream>
#include <opencv/highgui.h>
#include <opencv/cv.h>
#include "AdaptiveBackgroundLearning.h" int main(int argc, char **argv)
{
CvCapture *capture = 0;
int resize_factor = 100; if(argc > 1)
{
std::cout << "Openning: " << argv[1] << std::endl;
capture = cvCaptureFromAVI(argv[1]);
}
else
{
capture = cvCaptureFromCAM(0);
resize_factor = 50; // set size = 50% of original image
} if(!capture)
{
std::cerr << "Cannot initialize video!" << std::endl;
return 1;
} IplImage *frame_aux = cvQueryFrame(capture);
IplImage *frame = cvCreateImage(cvSize((int)((frame_aux->width*resize_factor)/100) , (int)((frame_aux->height*resize_factor)/100)), frame_aux->depth, frame_aux->nChannels);
cvResize(frame_aux, frame); /* Background Subtraction Methods */ /*** Default Package ***/
//bgs = new FrameDifferenceBGS;
//bgs = new StaticFrameDifferenceBGS;
//bgs = new WeightedMovingMeanBGS;
//bgs = new WeightedMovingVarianceBGS;
//bgs = new MixtureOfGaussianV2BGS;
//bgs = new MixtureOfGaussianV2BGS;
//bgs = new AdaptiveBackgroundLearning;
IBGS *bgs;
bgs= new AdaptiveBackgroundLearning; /*** DP Package (adapted from Donovan Parks) ***/
//bgs = new DPAdaptiveMedianBGS;
//bgs = new DPGrimsonGMMBGS;
//bgs = new DPZivkovicAGMMBGS;
//bgs = new DPMeanBGS;
//bgs = new DPWrenGABGS;
//bgs = new DPPratiMediodBGS;
//bgs = new DPEigenbackgroundBGS;
//bgs = new DPTextureBGS; /*** TB Package (adapted from Thierry Bouwmans) ***/
//bgs = new T2FGMM_UM;
//bgs = new T2FGMM_UV;
//bgs = new T2FMRF_UM;
//bgs = new T2FMRF_UV;
//bgs = new FuzzySugenoIntegral;
//bgs = new FuzzyChoquetIntegral; /*** JMO Package (adapted from Jean-Marc Odobez) ***/
//bgs = new MultiLayerBGS; /*** PT Package (adapted from Hofmann) ***/
//bgs = new PixelBasedAdaptiveSegmenter; /*** LB Package (adapted from Laurence Bender) ***/
//bgs = new LBSimpleGaussian;
//bgs = new LBFuzzyGaussian;
//bgs = new LBMixtureOfGaussians;
//bgs = new LBAdaptiveSOM;
//bgs = new LBFuzzyAdaptiveSOM; /*** LBP-MRF Package (adapted from Csaba Kertész) ***/
//bgs = new LbpMrf; /*** AV Package (adapted from Antoine Vacavant) ***/
//bgs = new VuMeter; /*** EG Package (adapted from Ahmed Elgammal) ***/
//bgs = new KDE; int key = 0;
while(key != 'q')
{
frame_aux = cvQueryFrame(capture);
if(!frame_aux) break; cvResize(frame_aux, frame); cv::Mat img_input(frame);
cv::imshow("input", img_input); cv::Mat img_mask;
cv::Mat img_bkgmodel;
bgs->process(img_input, img_mask, img_bkgmodel); // automatically shows the foreground mask image
//imshow("img_mask",img_mask);
//imshow("img_bkgmodel",img_bkgmodel);
if(!img_mask.empty())
imshow("img_mask",img_mask);
// do something key = cvWaitKey(33);
} delete bgs; cvDestroyAllWindows();
cvReleaseCapture(&capture); return 0;
}

配置文件background.vcxproj

<?xml version="1.0" encoding="utf-8"?>
<Project DefaultTargets="Build" ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
<ItemGroup Label="ProjectConfigurations">
<ProjectConfiguration Include="Debug|Win32">
<Configuration>Debug</Configuration>
<Platform>Win32</Platform>
</ProjectConfiguration>
<ProjectConfiguration Include="Release|Win32">
<Configuration>Release</Configuration>
<Platform>Win32</Platform>
</ProjectConfiguration>
</ItemGroup>
<ItemGroup>
<ClCompile Include="AdaptiveBackgroundLearning.cpp" />
<ClCompile Include="GMG.cpp" />
<ClCompile Include="main4.cpp" />
</ItemGroup>
<ItemGroup>
<ClInclude Include="AdaptiveBackgroundLearning.h" />
<ClInclude Include="GMG.h" />
<ClInclude Include="IBGS.h" />
</ItemGroup>
<PropertyGroup Label="Globals">
<ProjectGuid>{C9F9AAD6-4C2A-414F-ADBE-891F28F9E32F}</ProjectGuid>
<Keyword>Win32Proj</Keyword>
<RootNamespace>background</RootNamespace>
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
<ConfigurationType>Application</ConfigurationType>
<UseDebugLibraries>true</UseDebugLibraries>
<CharacterSet>Unicode</CharacterSet>
<UseOfMfc>false</UseOfMfc>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
<ConfigurationType>Application</ConfigurationType>
<UseDebugLibraries>false</UseDebugLibraries>
<WholeProgramOptimization>true</WholeProgramOptimization>
<CharacterSet>Unicode</CharacterSet>
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
</ImportGroup>
<ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
<Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
<Import Project="opencv_d.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
<Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
</ImportGroup>
<PropertyGroup Label="UserMacros" />
<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
<LinkIncremental>true</LinkIncremental>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
<LinkIncremental>false</LinkIncremental>
</PropertyGroup>
<ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
<ClCompile>
<PrecompiledHeader>
</PrecompiledHeader>
<WarningLevel>Level3</WarningLevel>
<Optimization>Disabled</Optimization>
<PreprocessorDefinitions>WIN32;_DEBUG;_CONSOLE;%(PreprocessorDefinitions)</PreprocessorDefinitions>
</ClCompile>
<Link>
<SubSystem>Console</SubSystem>
<GenerateDebugInformation>true</GenerateDebugInformation>
<AdditionalLibraryDirectories>%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
<AdditionalDependencies>%(AdditionalDependencies)</AdditionalDependencies>
</Link>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
<ClCompile>
<WarningLevel>Level3</WarningLevel>
<PrecompiledHeader>
</PrecompiledHeader>
<Optimization>MaxSpeed</Optimization>
<FunctionLevelLinking>true</FunctionLevelLinking>
<IntrinsicFunctions>true</IntrinsicFunctions>
<PreprocessorDefinitions>WIN32;NDEBUG;_CONSOLE;%(PreprocessorDefinitions)</PreprocessorDefinitions>
</ClCompile>
<Link>
<SubSystem>Console</SubSystem>
<GenerateDebugInformation>true</GenerateDebugInformation>
<EnableCOMDATFolding>true</EnableCOMDATFolding>
<OptimizeReferences>true</OptimizeReferences>
</Link>
</ItemDefinitionGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
</ImportGroup>
</Project>

 注意:在可执行文件下要有config文件夹

 效果如下:

1,摄像头

2,视频文件

opencv2.4.4 背景减除算法收集的更多相关文章

  1. 【计算机视觉】基于样本一致性的背景减除运动目标检测算法(SACON)

    SACON(SAmple CONsensus)算法是基于样本一致性的运动目标检测算法.该算法通过对每个像素进行样本一致性判断来判定像素是否为背景. 算法框架图 由上图可知,该算法主要分为四个主要部分, ...

  2. PHP 经典有趣的算法收集(面试题)

    1.一群猴子排成一圈,按1,2,…,n依次编号.然后从第1只开始数,数到第m只,把它踢出圈,从它后面再开始数,再数到第m只,在把它踢出去…,如此不停的进行下去,直到最后只剩下一只猴子为止,那只猴子就叫 ...

  3. 【计算机视觉】背景建模--Vibe 算法优缺点分析

    一.Vibe 算法的优点 Vibe背景建模为运动目标检测研究邻域开拓了新思路,是一种新颖.快速及有效的运动目标检测算法.其优点有以下两点: 1.思想简单,易于实现.Vibe通常随机选取邻域20个样本为 ...

  4. 基于SNMP的路由拓扑发现算法收集

    一.三层(网络层)发现 算法来源:王娟娟.基于SNMP的网络拓扑发现算法研究.武汉科技大学硕士学位论文,2008 数据结构: 待检路由设备网关链表:存放指定深度内待检路由设备的网关信息,处理后删除. ...

  5. js-数组算法收集版(转)

    不管是在面试中还是在笔试中,我们都会被经常问到关于javascript数组的一些算法,比方说数组去重.数组求交集.数组扰乱等等.今天抽点时间把javascript中的一些常用的数组算法做一下总结,以方 ...

  6. 数据结构 + 算法 -> 收集

    董的博客:数据机构与算法合集 背包问题应用(2011-08-26) 数据结构之红黑树(2011-08-20) 素数判定算法(2011-06-26) 算法之图搜索算法(一)(2011-06-22) 算法 ...

  7. 减治算法之寻找第K小元素问题

    一.问题描写叙述 给定一个整数数列,寻找其按递增排序后的第k个位置上的元素. 二.问题分析 借助类似快排思想实现pation函数.再利用递归思想寻找k位置. 三.算法代码 public static ...

  8. asp中的md5/sha1/sha256算法收集

    对于asp这种古董级的技术,这年头想找一些有用的资料已经不容易了,下面是一些常用的加密算法: md5 (将以下代码另存为md5.inc) <% Private Const BITS_TO_A_B ...

  9. Scala 大数据 常用算法收集

    一:IP转数字,用于比大小,用在求IP段范围中 def ip2Long(ip: String): Long = { val fragments = ip.split("[.]") ...

随机推荐

  1. poj City Horizon (线段树+二分离散)

    http://poj.org/problem?id=3277 City Horizon Time Limit: 2000MS   Memory Limit: 65536K Total Submissi ...

  2. Sublime Text 3 安装及简单配置

    Sublime Text 3, 一款不错的文本编辑器, 加上各种插件和IDE就能化身各种语言的编译器, 界面以及多种插件的灵活组合搭配更是让程序员们在码代码这种枯燥的生活中增加一点调剂. 下载地址 点 ...

  3. 1014: [JSOI2008]火星人prefix - BZOJ

    Description 火星人最近研究了一种操作:求一个字串两个后缀的公共前缀.比方说,有这样一个字符串:madamimadam,我们将这个字符串的各个字符予以标号:序号: 1 2 3 4 5 6 7 ...

  4. 明晰三种常见存储技术:DAS、SAN和NAS

    随着企业网络应用的时间和应用的数据量的加大,企业已经感觉到存储容量和性能落后与网络的应用发展需求,特别是流媒体企业,在这种应用条件下满足用户的存储需求的技术应用诞生,DAS.NAS和SAN三种存储技术 ...

  5. SpringJUnit4加载类目录下(src)和WEF-INF目录下的配置文件

    路径说明: 一.加载类目录下的配置文件 @RunWith(SpringJUnit4ClassRunner.class) @ContextConfiguration("classpath:ap ...

  6. [转载]Unity3D 游戏引擎之使用C#语言建立本地数据库(SQLITE)

    以前在开发中一直使用IOS源生的数据库,通过传递消息的形式在与Unity3D中进行交互.本文我在详细说说如何使用C#语言来在MAC 操作系统下创建Unity本地数据库,我是C#控哇咔咔--- 首先你需 ...

  7. PAT-乙级-1038. 统计同成绩学生(20)

    1038. 统计同成绩学生(20) 时间限制 250 ms 内存限制 65536 kB 代码长度限制 8000 B 判题程序 Standard 作者 CHEN, Yue 本题要求读入N名学生的成绩,将 ...

  8. javascript div z-index, input tabindex属性说明

    <html> <body> <form> 用户名: <input type="text" tabindex="1" / ...

  9. Redis hash数据类型操作

    Redis hash是一个string类型的field和value的映射表.一个key可对应多个field,一个field对应一个value.将一个对象存储 为hash类型,较于每个字段都存储成str ...

  10. VO,DTO,DO,PO的划分

    实体类(VO,DTO,DO)的划分   经常会接触到VO,DO,DTO的概念,本文从领域建模中的实体划分和项目中的实际应用情况两个角度,对这几个概念进行简析. 得出的主要结论是:在项目应用中,VO对应 ...