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通过对序列图像进行混合高斯建模，分离背景和前景目标。-Gaussian mixture modeling of image sequences, separation of background and foreground objects.
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GMM program that will help to implement the concept of gaussian mixture model
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This introduction to the expectation–maximization (EM) algorithm
provides an intuitive and mathematically rigorous understanding of
EM. Two of the most popular applications of EM are described in
detail: estimating Gaussian mixture models (GMMs),
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高斯拟合模型的C++实现，包含main和GMM.h实现,c++ implementation of Gaussian Mixture Model
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通过建立高斯混合模型用于运动目标检测，将视频帧检测为前景和背景-Target detection through the establishment of Gaussian mixture model for motion video frame detection for foreground and background
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利用混合高斯模型进行运动跟踪的源代码，vc++和opencv，需要有摄像头支持。-The use of Gaussian mixture model motion tracking the source code vc++ and opencv, camera support.
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opencv混合高斯模型实现的理论基础,比较有参考价值-The theory of the mixture gaussian model in opencv
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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
-Studied based on Gaussian mixture model of moving target detection technology, the analysis of the basic principles of Gaussian mixture model based on the use of an improved algorithm
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了适应跟踪过程中目标光照条件的变化，并对目标特征进行在线更新，提出一种将局部二元模式(LBP)
特征与图像灰度信息相融合，同时结合增量线性判别分析对目标进行跟踪的算法．跟踪开始前，为了获得比较准确的目标描述，使用混合高斯模型和期望最大化算法对目标进行分割；跟踪过程中，通过蒙特卡罗方法对目标区域和背景区域进行采样，并更新特征空间参数．得到目标和背景的最优分类面；最后使用粒子滤波器结合最优分类面对目标状态进行预测．通过光照变化的仿真视频和自然场景视频的跟踪实验，验证了文中算法的有效性．-Trac
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Finally, probability analysis, based on the chosen database, is performed and
judgment whether the person is recognized is pronounced. Two different modeling
techniques can be suggested for purposes of person identification or verification. The
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位图图像稳定区域分割的种子点选取条件，区域定义 区域分割 高斯混合模型 高斯分布 种子点选取 阈值选取 灰度范围-Bitmap image stabilization region segmentation of the seed point selection conditions, regional definition Region segmentation Gaussian mixture model Gaussian distribution The seed point select
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内含visual C++和MATLAB代码，利用高斯呼喝模型进行背景建模，自适应确定高斯分量的个数，由Z.Zivkovic开发，相关文章是 Improved adaptive Gausian mixture model for background subtraction-Containing visual C++ and MATLAB code, the use of Gaussian background modeling feeding model, adaptive determine
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The Gaussian mixture probability hypothesis density filter (GM-PHD Filter) was proposed recently for jointly estimating the time-varying number of targets and their states a noisy sequence of sets of measurements. - The Gaussian mixture probability
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运用高斯混合模型，识别车辆，分割车辆，检测车流量，运算很快，效果不错-Using the gaussian mixture model, identification of vehicles, vehicle segmentation, detection and traffic operation soon, effect is good
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This collection of MATLAB files perform operations on Gaussian mixture models (GMMs) and Gaussian kernels (ie, Parzen windows). These utilities do evaluation, sampling, multiplication, convolution, linear transformation, mixture reduction, etc. Prese
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隐马尔科夫模型工具箱，readme文档介绍了该工具箱的使用方法-Hidden Markov Model (HMM) Toolbox written by Kevin Murphy (1998).
Seehttp://www.ai.mit.edu/~murphyk/Software/hmm.html for details.
Models
dhmm = HMM with discrete output
mhmm = HMM with mixture of G
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基于高斯混合模型和EM（Expectation Maximization）算法的SAR影像变化监测算法，并附带示例。总体思路是首先将两个时期的SAR影像做log和ratio运算，生成差分影像，然后通过EM算法估计高斯混合模型的参数，最后根据高斯混合模型最大概率，生成变化监测结果。-Unsupervised change detection method for SAR images using EM algorithms of Gaussian mixture model
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Just like EM of Gaussian Mixture Model, this is the EM algorithm for fitting Bernoulli Mixture Model.
GMM is useful for clustering real value data. However, for binary data (such as bag of word feature) Bernoulli Mixture is more suitable.
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混合高斯背景建模程序，实现视频图像实时背景建模和目标跟踪-Gaussian mixture background modeling procedures to achieve real-time video image background modeling and target tracking
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打开视频文件，通过运用高斯混合模型对运动物体建模，统计运动数量，通过kalman滤波进行目标跟踪。(Open the video file, through the use of Gaussian mixture model of moving objects modeling, statistics, the number of motion, Kalman filtering target tracking.)
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