对于静态背景层，采用基于颜色特征的个数较少的混合高斯模型对背景建模；
A Gaussian Mixture Model based on color feature is adopted in static layer.
采用自适应高斯混合方法为背景建模的难点是对背景模型的维持与更新。
Taking the method of adaptive Gaussian mixture method can make model for background meanwhile it is a difficult point to maintain and update background model.
本文将高斯一马可夫模型推广到参数X具有附加信息的情况，并给出了它的混合估计（?）
This paper extends the Gauss-Marcov model to the case of parameter X with additional information and gives its mixed estimation X.
针对语音激活检测的鲁棒性问题，提出在非平稳噪声环境下使用基于复高斯混合模型的鲁棒语音激活检测算法。
In order to improve the robustness of voice activity detection (VAD), the use of an algorithm based on complex Gaussian mixture model under nonstationary noisy environments was presented.
针对马尔可夫随机场在红外图像分割方面存在的问题，给出了一种基于混合高斯模型的三马尔可夫场红外图像分割算法。
Due to the problems to infrared image segmentation using Markov random fields, a method for infrared image segmentation based on triplet Markov fields using mixture gauss model was proposed.
而在各高斯分量概率密度互不重叠的条件下，使用动态簇算法(DC)则可快速而精确地估计出混合高斯模型参数。
And if there are no overlaps between each Gaussian component, parameters of Gaussian mixture PDF model can be exact estimated quickly with the dynamic cluster algorithm (DC).
提出了一种基于表面法向的高斯混合模型的距离图像分割算法。
A range image segmentation algorithm based on Gaussian mixture model of surface normal is proposed.
高斯混合密度降解模型(GMDD)是一种基于稳健统计理论的层次聚类方法。
Gaussian Mixture Density Modelling and Decomposition (GMDD) is a hierarchical clustering method based on robust statistical theory.
提出一种鲁棒自适应表面模型，该模型中每个像素值的变化过程由一混合高斯分布描述。
A robust and adaptive appearance model is proposed, in which the value of each pixel over time is modeled by a mixture of Gaussians.
在算法方面，高斯混合模型(GMM)是目前最成功的一种说话人识别模型。
In algorithm ways, Gaussian mixture model (GMM) is the most successful speaker recognition model at present.
该算法使用混合高斯模型表示粒子，在每个时刻的修正步骤之后，采用EM算法对粒子进行重新拟合。
It USES Gassian mixture model to represent particles and adopts EM algorithm to refit particles after correction step at each time.
从特征值处理和模型补偿两方面考虑，提出了基于高斯混合模型的加权特征补偿变换的抗噪声方法。
Based on feature processing and model compensation, a weighted features compensation transformation method based on GMM for robust speaker verification was proposed.
混合高斯模型是背景对消中一种非常有效的方法。
Mixture Gaussian model is one of background subtraction methods.
本文将混合高斯分布应用于一种非齐次隐含马尔可夫模型——简化的基于段长分布的隐含马尔可夫模型。
Gaussian Mixture Distribution is introduced into one kind of inhomogeneous Hidden Markov model-simplified Duration Distribution Based HMM in this paper.
针对海事场景背景复杂、干扰大等困难，提出了改进的混合高斯背景模型及运动检测方法。
Because the marine scene is complicated and interferential, a modified mixture Gaussians approach and a moving detection method are suggested.
用混合高斯模型得到运动人体的区域，通过卡尔曼滤波对人体进行跟踪，并利用人体的颜色信息进行识别。
Moving areas about human are segmented by using hybrid Gaussian model as background, tracked by Kalman filter, and recognized by using a color-based model.
为了解决传统高斯混合模型（GMM）对初值敏感，在实际训练中极易得到局部最优参数的问题，提出了一种采用微粒群算法优化GMM参数的新方法。
The traditional training methods of Gaussian Mixture Model(GMM) are sensitive to the initial model parameters, which often leads to a local optimal parameter in practice.
高斯混合模型(GMM)已广泛地应用于文本无关的说话人识别系统，该方法具有简单高效的特点。
Gaussian mixture model (GMM) has been widely used for text-independent speaker recognition. This method has simple and efficient character.
本文介绍了常用的三种肤色检测模型：统计颜色模型、色度空间模型和高斯混合模型。
This paper introduced three skin-color detecting model: Statistical color model, Chroma Space model and Gaussian Mixture model.
再针对具体的自动标注过程，建立了基于高斯混合模型的自动图像标注模型。
And then, taking into account the specific process of automatic image annotation, we built the automatic image annotation model based on Gaussian mixture model.
在识别过程中，首先假设各乐器的先验概率相同，根据高斯混合模型得出的后验概率确定待识别乐器所属的种类。
In the process of recognition, the prior probability is supposed to be the same, the posterior probability is calculated according to GMM, and then the instrument class is determined.
但如果GMM模型的高斯混合分量的数目比较多时，整个模型运算的复杂度会比较大。
However, if it has a large number of Gaussians in GMM, it leads to a large complexity of computation.
实验结果表明，该方法与传统高斯混合背景模型相比，有较好的学习能力与稳定性，能提高运动目标检测的正确率。
Experimental results show that compared with moving object detection approach based on conventional Gaussian mixture model, it has a desirable stability and learning ability.
本文在前人工作的基础上，研究了基于小波变换和高斯混合模型(GMM)的病态嗓音识别系统。
Based on the work of predecessors, the paper has studied on the system of pathological voice recognition based on the wavelet transformation and Gaussian mixes model (GMM).
对于GMM模型，采用高斯混合数为64时有较好的识别率。
For the model of GMM, there is a good result for choosing 64 mixtures GMM.
文中针对混合高斯模型不能应对光线突变的问题，提出了一种改进的背景模型。
This paper proposes an improved background subtraction method based on Gaussian mixture background model which can not deal with the problem of scene light rapid change.
首先建立高斯混合的灰度统计模型，运用MDL准则自动确定类别的数目。
Gaussian mixture model is firstly built as the statistical model for the intensity image, with an estimation of index number using MDL.
混合高斯模型在训练背景模型的过程中效果良好，但其收敛速度较慢。
The effect of Gaussian Mixture model used in training background model is good, but its convergence velocity is low.
混合高斯模型在训练背景模型的过程中效果良好，但其收敛速度较慢。
The effect of Gaussian Mixture model used in training background model is good, but its convergence velocity is low.
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