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sho.rar
- 基于c++的,运用opencv开发包的高斯混合模型,用于视频中运动物体的检测,Based on c++ And use the development package opencv Gaussian mixture model for moving objects in video detection
code.rar
- 视频运动物体检测,采用混合高斯分布建立背景模型及差分方法对背景模型进行更新,Sports video object detection, adopt a mixed Gaussian distribution model and set up the background difference method to update the background model
bodymotiondetection
- 学习opencv图像处理中人体目标跟踪的一些很有用的资料,主要是讲camshift,meanshift和高斯混合模型。-Learning opencv image-processing for target tracking in the human body a number of very useful information, mainly speaking camshift, meanshift and Gaussian mixture model.
CvBSLibGMM
- 改进的高斯混合模型用于运动目标的检测和分割,利用C++和matlab混合编程.-Improved Gaussian mixture model for moving object detection and segmentation, the use of C++ and matlab programming mixed.
Em
- 通过em算法实现对数据的高斯混合模型的分类-Em algorithm through implementation of data Gaussian mixture model classification
IGMM
- 这是一篇经典的论文,基于混合高斯的数学模型应用在视频处理中,进行的移动物体提取-Multi-Gaussian model is the detection of moving targets in a background reduction method, which is achieved using matlab
em
- 混合高斯概率密度模型,其参数估计可以通过期望最大化( EM) 迭代算法获得。-EM estimation parameters Gaussian mixture processes
GMM
- 利用K-高斯混合模型提取视频的前景信息。-The use of K-Gaussian mixture model for the future of video information extraction
mixture_of_gaussians
- 这是一个视频图像处理的程序,通过混合高斯分布来建立背景模型,并且提取了运动目标,效果不错!-mixture of gaussians
basedoncolorsegment
- 为了提高非结构化道路识别算法的有效性,提出了一种道路分割的新方法,建立了道路区域和非道路区域混合高斯彩色模型,根据像素隶属于彩色模型的概率进行基于彩色信息道路 -In order to improve the effectiveness of unstructured road recognition algorithm presents a new method of road segmentation and establish the way of regional and off-roa
sMOG_ChangeUpdateRate_DilationErosion
- simulink下封装的混合高斯的s-funcion函数。用于模型模块的搭建。-simulink package under the Gaussian mixture of s-funcion function. The structures used to model the module.
xiaobo
- .首先,建 立背景的混合高斯分布模型和阴影颜色模型,通过差分法提取前景区域并结合Gabor小 波纹理特征分析找出潜在的阴影点;然后通过阴影颜色模型对这些潜在的阴影点进行颜 色分析;最后通过后续处理,找出真正的阴影区域-. First of all, to establish the background Gaussian mixture distribution model and the shadow color model, by differential extraction
GMM_background_src
- 基于有限混合高斯模型的数据分类 1、使用基于有限高斯混合模型的EM算法对数据样本进行归类 2、使用C++或者Matlab语言编程环境实现该算法,并用给定的数据包对算法的正确性进行检验 -Gaussian mixture model based on limited data classification 1, using the finite Gaussian mixture model based on EM algorithm to classify the data sam
mixture_of_gaussians
- 这个程序是基于混合高斯背景模型的运动目标检测算法,m文件和所用视频放到matlab的工作目录下即可运行-This program is based on the Gaussian mixture background model of moving target detection algorithm, m, and used video files into matlab working directory to run
motion-detection-techniques
- 研究了基于混合高斯模型的运动目标检测技术,在分析了混合高斯模型的基本原理的基础上,使用了一种改进的混合高斯模型更新算法.在Visual C++6.0中利用OpenCV完成了相关算法,成功地提取出了运动目标和实验场景的背景,验证了该改进的混合高斯模型更新算法的可行性-OpenCV-based motion detection techniques I have read some articles, I feel you can, share
高斯混合模型EM算法MATLAB程序
- 在高斯混合模型上实现聚类问题的算法。将2个高斯混合,然后尝试学习两个高斯混合后的参数。(Algorithm for clustering problem on Gauss mixture model. Mix the 2 Gauss and then try to learn the parameters after the two Gauss mixing.)
一问 + 二问 VIBE_Code
- 用混合高斯模型进行背景处理,并能过滤微小的扰动,适用于动态背景(Use the mixed Gaussian model for background processing and to filter tiny perturbations for dynamic background)
改进的高斯混合背景模型的实现
- 利用改进的高斯混合模型对前景目标的提取有较好的作用,这是基于OpenCV的C++程序,请安装OpenCV库进行调试(The improved Gauss mixture model has a good effect on foreground target extraction. This is a C++ program based on OpenCV. Please install OpenCV library for debugging)
Gaussian Mixture Model Ellipsoids
- 基于2个一维高斯模型组成的多维混合高斯模型,采用Python进行编程(Multidimensional mixed Gauss model based on 2 one-dimensional Gauss models and programming with Python)
gaussianBkModelTest
- 采用混合高斯模型,实现对监视背景的建模,有利于下一步运动目标的检测(The mixed Gauss model, modeling of monitoring background, is conducive to the detection of moving target next)