Using unsupervised learning of a finite Dirichlet mixture model to improve pattern recognition applications

Nizar Bouguila; Djemel Ziou

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Using unsupervised learning of a finite Dirichlet mixture model to improve pattern recognition applications

机译：使用有限Dirichlet混合模型的无监督学习来改善模式识别应用

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摘要

Mixture modeling is the problem of identifying and modeling components in a given set of data. Gaussians are widely used in mixture modeling. At the same time, other models such as Dirichlet distributions have not received attention. In this paper, we present an unsupervised algorithm for learning a finite Dirichlet mixture model. The proposed approach for estimating the parameters of a Dirichlet mixture is based on the maximum likelihood (ML) expressed in a Riemannian space. Experimental results are presented for the following applications: summarization of texture image databases for efficient retrieval, and human skin color modeling and its application to skin detection in multimedia databases.

机译：混合物建模是在给定数据集中识别和建模组件的问题。高斯广泛用于混合模型。同时，其他模型（例如Dirichlet分布）并未受到关注。在本文中，我们提出了一种用于学习有限Dirichlet混合模型的无监督算法。所提出的估计狄利克雷混合物参数的方法是基于在黎曼空间中表达的最大似然（ML）。给出了以下应用的实验结果：用于有效检索的纹理图像数据库的汇总，以及人类肤色建模及其在多媒体数据库中皮肤检测中的应用。

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来源
《Pattern recognition letters》 |2005年第12期|p.1916-1925|共10页
作者
Nizar Bouguila; Djemel Ziou;
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作者单位

Departement d'Informatique, Faculte des Sciences, Universite de Sherbrooke, Sherbrooke, QC, Canada J1K 2R1;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类自动化技术及设备;
关键词
dirichlet distribution; mixture modeling; image summarization for efficient retrieval; human skin detection;

机译：狄利克雷分布;混合建模;有效的图像汇总;有效的人体皮肤检测;

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专利

1. Unsupervised learning of finite full covariance multivariate generalized Gaussian mixture models for human activity recognition [J] . Najar Fatma, Bourouis Sami, Bouguila Nizar, Multimedia Tools and Applications . 2019,第13期

机译：用于人类活动识别的有限全协方差多元广义高斯混合模型的无监督学习
2. Unsupervised learning of finite full covariance multivariate generalized Gaussian mixture models for human activity recognition [J] . Najar Fatma, Bourouis Sami, Bouguila Nizar, Multimedia Tools and Applications . 2019,第13期

机译：有限的充分协方差多变量广义高斯混合模型的无监督学习人类活动识别
3. Unsupervised learning of a finite discrete mixture: Applications to texture modeling and image databases summarization [J] . Nizar Bouguila, Djemel Ziou Journal of visual communication & image representation . 2007,第4期

机译：有限离散混合的无监督学习：在纹理建模和图像数据库摘要中的应用
4. Unsupervised Learning of a Finite Discrete Mixture Model Based on the Multinomial Dirichlet Distribution: Application to Texture Modeling [C] . Nizar Bouguila, Djemel Ziou International Workshop on Pattern Recognition in Information Systems . 2004

机译：基于多项式Dirichlet分布的有限离散混合模型的无监督学习：纹理建模应用
5. Dirichlet process mixture modeling: Hidden Markov mixture models and multi-task compressive sensing [D] . Qi, Yuting 2009

机译：Dirichlet过程混合物建模：隐马尔可夫混合物模型和多任务压缩感测
6. From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering [O] . Sylvia Frühwirth-Schnatter, Gertraud Malsiner-Walli -1

机译：从这里到无限：基于模型的聚类中的稀疏有限与Dirichlet过程混合
7. Unsupervised Learning of Finite Mixture Models using Mean Field Games [O] . Sergio Pequito, A. Pedro Aguiar, Bruno Sinopoli, 2016

机译：有限混合模型的无监督学习使用平均场比赛

Using unsupervised learning of a finite Dirichlet mixture model to improve pattern recognition applications

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