搜索资源列表
GaussEm
- 关于高斯混合模型（GMM）的matlab源代码-on Gaussian mixture model (GMM) Matlab source code
gm
- 改进的gmm（高斯混合模型）算法，是单一高斯几率密度函数的衍生-Improved gmm (GMM) algorithm, a single Gaussian probability density function of the derivative
EMGMMSeg
- 对图像进行GMM（混合高斯）拟合后用EM算法进行分割-Image GMM (Gaussian Mixture) after fitting algorithm using EM Segmentation
GMM-matlab
- 关于高斯混合模型（GMM）的matlab源代码：-On the Gaussian mixture model (GMM) of the matlab source code:
gmm_test
- 使用EM算法模拟高斯混合模型（GMM）的构成-Analog EM algorithm using Gaussian mixture model (GMM) the composition of
GMM_Purdue
- 基于混合高斯模型（GMM）的无监督聚类算法，希望对大家有帮助-Based on Gaussian mixture model (GMM) unsupervised clustering algorithm, I hope it would have help to you！
gmmMatlab
- 关于高斯混合模型（GMM）的matlab源代码-是用于训练分类的不错的源代码-On the Gaussian mixture model (GMM) of the matlab source code- is used to train a good classification of the source code
BGFG_CODEBOOK
- 基于码书的运动目标检测是和混合高斯模型（MoG，GMM）类似的而简单有效的背景剪除方法，附件是VC++6.0编写的基于码书的运动目标检测，可直接读取摄像头，也可改为读取硬盘视频文件，需安装Opencv1.1-Codebook-based moving target detection and Gaussian mixture model (MoG, GMM) and a similar cut off the background si
GMMandSGM
- 一篇详细的介绍高斯混合模型（GMM）参数优化及实现的文档，有实例, 包括VC及matlab 实现。初始学者一看就能懂-A detailed descr iption of Gaussian mixture model (GMM) parameter optimization, and implementation documentation, including the VC and the matlab implementation
mixture_of_gaussians
- 混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。-training video with GMM model ,then get the background,and store the picture in your computer.
BGFG_CODEBOOK
- 基于码书的运动目标检测是和混合高斯模型（MoG，GMM）类似的而简单有效的背景剪除方法，附件是VC++6.0编写的基于码书的运动目标检测，可直接读取摄像头，也可改为读取硬盘视频文件，需安装Opencv1.1，-Codebook-based moving target detection and Gaussian mixture model is (MoG, GMM) and a similar cut off the backgroun
GMM
- 无监督混合高斯模型（GMM）的EM估计，含两篇IEEE论文的源码-This is a set of MATLAB m-files implementing the mixture fitting algorithm described in the paper M. Figueiredo and A.K.Jain, "Unsupervised learning of finite mixture models", IEEE
GMM_kmeans_mix
- 用于说话人识别（声纹识别）训练过程或识别过程的高斯混合模型-GMM model for training process or testing process of Speaker recognition
clustering
- 使用K-means，混合高斯模型（GMM），层次聚类算法实现的多类别数据的聚类。内含详细的实验报告。-Using K-means, Gaussian mixture model (GMM), hierarchical clustering algorithm to achieve multi-class data clustering. Including a detailed lab report.
GMM
- 一种改进的混合高斯模型（GMM）算法，加入形态学滤波与团块处理算法，运动目标提取效果良好。(An improved hybrid Gauss model (GMM) algorithm, which combines morphological filtering and blob processing algorithm, achieves good moving target extraction.)
GMM
- 此算法实现高斯混合，可以对初始聚类算法选择c均值和EM，可以实现密度估计和分类。(This GMM algorithm can estimate the density and class, the initial steps can select the C-mean and EM.)
gmm
- 基于高斯混合模型的运动目标检测，opencv平台，直接可用(Moving target detection of Gauss mixed model)
HMM1
- 在VC6.0平台上进行编写的，包括隐马尔科夫模型（HMM）和混合高斯模型（GMM）在内的用于模板训练的算法。(The algorithm for template training is written on VC6.0 platform, including hidden Markov model (HMM) and mixed Gauss model (GMM).)
RCY-GMMtest1
- 高斯混合模型（GMM,Gaussian Mixture Model）参数如何确立这个问题，详细讲解期望最大化（EM,Expectation Maximization）算法的实施过程。(How to establish the parameters of Gauss mixture model and explain the implementation process of the expectation maximization al
基于高斯混合模型（GMM）的说话人识别matlab
- 基于GMM的话者识别matlab程序，训练运行train.m,识别运行recog.m(speaker identification system based on GMM)