Modal Trajectory Estimation Using Maximum Gaussian Mixture
نویسندگان
چکیده
منابع مشابه
Maximum likelihood estimation of Gaussian mixture models using stochastic search
Gaussian mixture models (GMM), commonly used in pattern recognition and machine learning, provide a flexible probabilistic model for the data. The conventional expectation–maximization (EM) algorithm for the maximum likelihood estimation of the parameters of GMMs is very sensitive to initialization and easily gets trapped in local maxima. Stochastic search algorithms have been popular alternati...
متن کاملSpeech quality estimation using Gaussian mixture models
We propose a novel method to estimate the quality of coded speech signals. The joint probability distribution of the subjective mean opinion score (MOS) and perceptual distortion feature variables is modelled using a Gaussian mixture density. The feature variables are sifted from a large pool of candidate features using statistical data mining techniques. We study what combinations of features ...
متن کاملImage Segmentation using Gaussian Mixture Model
Abstract: Stochastic models such as mixture models, graphical models, Markov random fields and hidden Markov models have key role in probabilistic data analysis. In this paper, we used Gaussian mixture model to the pixels of an image. The parameters of the model were estimated by EM-algorithm. In addition pixel labeling corresponded to each pixel of true image was made by Bayes rule. In fact,...
متن کاملGaussian Mixture Model estimation
One of the keystones of the canceled BTeV experiment (proposed at Fermilab’s Tevatron) was its sophisticated threelevel trigger. The trigger was designed to reject 99.9% of lightquark background events and retain a large number of B decays. The BTeV Pixel Detector provided a 3-dimensional, high resolution tracking system to detect B signatures. The Level 1 pixel detector trigger was proposed as...
متن کاملMulti-modal Background Subtraction Using Gaussian Mixture Models
Background subtraction is a common first step in the field of video processing and it is used to reduce the effective image size in subsequent processing steps by segmenting the mostly static background from the moving or changing foreground. In this paper previous approaches towards background modeling are extended to handle videos accompanied by information gained from a novel 2D/3D camera. T...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Automatic Control
سال: 2013
ISSN: 0018-9286,1558-2523
DOI: 10.1109/tac.2012.2211439