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利用OPENCV來實現高斯混合模型的背景相減
- 利用OPENCV來實現高斯混合模型的背景相減，可看到當前影像、前景及背景-OPENCV to achieve using GMM background subtraction, we can see the current image, foreground and background
GmmDetector
- Cuda GMM detector write on visual c-Cuda GMM detector write on visual c++
GMM-modeling-and-EM
- 介绍Opencv这个图像处理库环境下的GMM建模与EM算法，从数学的角度深入分析高斯建模和EM算法-Introduce the the Opencv this image processing GMM modeling the EM algorithm in the library environment, in-depth analysis from a mathematical point of the Gaussian model and the EM algorithm
CG11
- 基于高斯的背景建模，更改文件路径，载入AVI视频，运行，出现3个窗口，分别为视频、背景模型和前景-gmm
gg
- Its a GMM code gmr, matrix, vector etc codes are very useful
gmm
- 混合高斯算法实现及一些自己对高斯混合模型的理解。-Gaussian mixture algorithm and some experience
C-code-of-GMM
- OpenCV中，利用C语言写的GMM模型的代码。-OpenCV, the use of the GMM model code written in C language.
GMM
- 运用OpenCV2.0编辑混合高斯背景建模，能够较好的识别四个视频中的运动前景和背景，在一定程度的背景复杂度下，能够较准确检测。-The use OpenCV2.0 edit Gaussian mixture background modeling, and better identification of four video movement in the foreground and background, the background of a certain degree of com
GMM
- 使用openCV写的高斯混合模型前景分离作业。-Extract the foreground from video sequence using Gaussian Mixture Model（GMM）with openCV.
GMM
- 是opencv 混合高斯模型的原函数，并进行了修改可以实现前景提取并进行背景建模-opencv GMM
person-detection
- 采用混合高斯模型和codebook分别进行背景建模，实现行人检测-person detection, GMM and codebook
GMm
- 混合高斯模型在运动检测中的应用，检测视频中的运动物体，做出其背景图像和前景图像-Gaussian mixture model in motion detection to detect moving objects in the video to make the background image and the foreground image
gmm-cv
- OpenCV_基于混合高斯模型GMM的运动目标检测。内附监测监控视频，方便测试使用。-OpenCV_ GMM Gaussian mixture model based moving target detection. Included monitoring surveillance video, easy testing.
GMM
- 高斯混合滤波建模，基于opencv，用于背景建模，前景检测-Gaussian mixture filter modeling, based on opencv, for background modeling, foreground detection
Gaussian-mixture-model
- 混合高斯模型GMM EM算法，建模效果好，可以用于行为识别-Gaussian mixture model GMM EM algorithm, modeling effect, can be used for behavior recognition
GMM-GMR-v2.0
- 利用混合高斯模型对背景图像进行建模，所谓“混合高斯”的意思就是每个像素都是由多个单高斯分布混合组成的。-Name of the file which the classifier is loaded. Only the old haar classifier (trained by the haar training application) and NVIDIA s nvbin are supported for HAAR and only new type of OpenCV XML ca
OneCutWithSeeds_v1.03
- one cut 算法是微软研究院发表的一篇关于前背景图像分割论文，用户只需简单地交互，即可快速分割前背景，代码比较清晰，内部graph cut和gmm等一些算法可以拿来学习或借鉴。-one cut algorithm is the Microsoft Research published a paper on the front background image segmentation, the user simply interact, you can quickly split befor
背景差GMM
- opencv，vs2010 利用混合高斯模型，得到运动前景，与静态背景(Opencv and VS2010 use hybrid Gauss model to obtain motion foreground and static background)
Gmm
- 高斯混合模型,利用Ｃ++ OEPNCV来完成(This is a GMM model using C++ opencv to deal with it)