gaussian mixture model

In real-time platform, the Gaussian mixture model (GMM) with the calculation of the effectiveness and easy to realize benefits.

Gaussian mixture model(GMM) has been widely used for text-independent speaker recognition. This method has simple and efficient character.

Gaussian mixture model is firstly built as the statistical model for the intensity image, with an estimation of index number using MDL.

Finally, use Gaussian mixture model to determine the region whether it's hair region or not.

Gaussian Mixture Model assumes the independence between data while Hidden Markov Model allows Markov assumption in a data series.

The initial background is established using the traditional Gaussian mixture model with a global learning rate.

A multi-step clustering algorithm with transformation-based and diagonal-covariance Gaussian mixture model (GMM) is advanced.

This paper introduced three skin-color detecting model: Statistical Color Model, Chroma Space Model and Gaussian Mixture Model.

The effect of Gaussian Mixture Model used in training background model is good, but its convergence velocity is low.

We use the fixed-arithmetician DSP chip ( chipboard ) in the DSP, the algorithm of recognition is Gaussian mixture model.

Then, built the color model for background and foreground utilizing the GMM (Gaussian mixture model).

Based on finite Gaussian mixture model of the EM algorithm source code, which has run reports and experimental results.

The three Frames subtraction and the background subtraction of Gaussian mixture model are researched.

Gaussian mixture model (GMM) is first trained for grass pixel, the grass distribution is then computed based on the trained GMM.

This paper proposed an improved moving objects detection method based on Gaussian mixture model.

A Gaussian Mixture Model based on color feature is adopted in static layer.

Algorithm EM and Its Initialization in Gaussian-Mixture-Model Based Clustering

Probability Density Function Approximation Using Gaussian Mixture Model

Study of Gaussian mixture model for image wavelet coefficients

MRI Segmentation via Active Contour Model Improved with Gaussian Mixture Model

Study of image denoising based on gaussian mixture model in wavelet domain and median filter

Speech Separation Based on Gaussian Mixture Model Probability Density Function Estimation

Motion Segmentation via On-line Gaussian Mixture Model and Texture

A New Parameter Estimation Algorithm of Gaussian Mixture Model

Multiple region parallel region growing for image segmentation based on Gaussian-mixture model

Speaker Identification Based on Classify Feature Sub-space Gaussian Mixture Model and Neural Net Fusion

A Study of EM Learning Algorithm Based on Gaussian Mixture Model

Gaussian mixture model training method based on genetic algorithms and fuzzy approach

An Approach for Estimating Parameters in Gaussian Mixture Model Based on Maximum Cross Entropy

MR Image Segmentation of Left Ventricle Based on the Multi-information Gaussian Mixture Model

TWS Tracking Techniques Based on Adaptive Gaussian Mixture Model in Phased Array Radar

Image denoising method based on adaptive Gaussian mixture model in wavelet domain

An unsupervised rough clustering method based on gaussian mixture model

Image Stabilization Based on Adaptive Gaussian Mixture Model

New linear discriminant analysis based on Gaussian mixture model

A Range Image Segmentation Algorithm Based on Gaussian Mixture Model

Speaker recognition system based on Gaussian mixture model

Video Object Segmentation Based on Gaussian Mixture Model

Regional Color Transfer Based on Gaussian Mixture Model