搜索资源列表
高斯混合模型原理
- 能了解混合模型的每一步操作
Matlab.Gaussian.mixture.model.
- 基于Matlab的高斯混合模型的算法实现，该程序可以实现对图像处理的功能,Matlab based on the Gaussian mixture model algorithm, the program can achieve the functions of image processing
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.
xml_toolbox-3.2.1-matlab-7.0-R14
- 高斯混合模型的matlab的实现，但是不包含em算法在里面，但是有版权，注意阅读内容-Gaussian mixture model of the matlab implementation, but does not include the em algorithm inside, but has the copyright and pay attention to read the content
EM_init_kmeans
- 高斯混合模型参数初始化程序，在对高斯混合模型的建立之前采用KMEANS算法进行初始化-Gaussian mixture model parameter initialization procedure, in the Gaussian mixture model is initialized before the algorithm used KMEANS
GMM
- 高斯混合模型，有详细的说明，而且有程序,希望下载，很有帮助的！-GMM including explanation and programs
demo
- 稳健点集配准的高斯混合模型程序。可用于轮廓提取后的图像配准。-Robust point set registration process Gaussian mixture model. After the contour extraction can be used for image registration.
EM
- 利用Matlab编程验证用EM算法估计的高斯混合模型的相关参数的性能。-Validate the use of Matlab programming estimated using EM algorithm for Gaussian mixture model parameters related to the performance.
交叉熵优化高斯混合模型
- matlab最大似然优化与交叉熵(CE)多高斯混合估计算法的应用(Maximum Likelihood Optimization and Cross Entropy (CE) Multi - Gaussian Mixture Estimation Algorithm)
高斯混合模型GMM-latentSpace-v2.0
- 用于背景建模实现视频运动目标分割 与目标跟踪算法(For background modeling, video moving object segmentation and object tracking algorithm)
mixture_of_gaussians
- 采用高斯混合模型来对目标进行前景检测，并用MATLAB实现。(The Gauss mixture model is used to detect the foreground of the target, and it is implemented by MATLAB.)
EM_GM_fast
- 高斯混合模型中的EM算法（就不完整数据的极大似然估计）应用(EM algorithm in Gauss mixture model)
GMM
- 高斯混合聚类的python实现代码，里面有data的demo(Python implementation code of Gauss mixed clustering)
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)
GMMs
- function对数据EM算法进行fit，并对产生的高斯混合模型的最大似然估计进行绘图。输出结构体obj，带有高斯混合模型的参数mu，sigma。(Function carries out fit for data EM algorithm, and draws the maximum likelihood estimation of the Gauss mixture model. The output structure is obj, with the parameter mu and s
GMM
- 实现了EM算法对高斯混合模型进行聚类，并将聚类结果用图像展示出来，希望对混合模型的朋友有用。(The EM algorithm is implemented to cluster the Gauss mixture model, and the clustering results are displayed with images, hoping to be useful to friends of the mixed models.)
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 algorithm in detail.)
GMM_test1
- 高斯混合模型的前景提取代码，本人测试可用。(Gauss mixture model of the foreground extraction code)
3-基于高斯混合模型的语音识别
- 基于高斯混合模型的语音识别，有完整的数据集和matlab代码(Speech recognition based on Gaussian mixture model, complete data set and matlab code)
GMM-HMRF
- 基于高斯混合模型和隐马尔科夫模型的图像分割算法(Image segmentation algorithm based on Gaussian mixture model and hidden Markov model)