Efficient Bayesian approach to saliency detection based on Dirichlet process mixture

Navid Rabbani; Behzad Nazari; Saeid Sadri; Reyhaneh Rikhtehgaran

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Efficient Bayesian approach to saliency detection based on Dirichlet process mixture

机译：基于Dirichlet过程混合的有效贝叶斯显着性检测方法

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Saliency detection has shown a great role in many image processing applications. This study introduces a new Bayesian framework for saliency detection. In this framework, image saliency is computed as product of three saliencies: location-based, feature-based and centre-surround saliencies. Each of these saliencies is estimated using statistical approaches. The centre-surround saliency is estimated using Dirichlet process mixture model. The authors evaluate their method using five different databases and it is shown that it outperform state-of-the-art methods. Also, they show that the proposed method has a low computational cost.

机译：显着性检测已在许多图像处理应用程序中发挥了重要作用。本研究介绍了一种用于显着性检测的新贝叶斯框架。在此框架中，图像显着度是三个显着度的乘积：基于位置，基于特征和围绕中心的显着度。这些显着性均使用统计方法进行估算。使用Dirichlet过程混合模型估计中心周围的显着性。作者使用五个不同的数据库评估了他们的方法，结果表明该方法的性能优于最新方法。而且，他们表明所提出的方法具有较低的计算成本。

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《Image Processing, IET》 |2017年第11期|1103-1113|共11页
作者
Navid Rabbani; Behzad Nazari; Saeid Sadri; Reyhaneh Rikhtehgaran;
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正文语种 eng
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关键词
Bayes methods; image processing; statistical analysis;

机译：贝叶斯方法;图像处理;统计分析;

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1. Multimode process data modeling: A Dirichlet process mixture model based Bayesian robust factor analyzer approach [J] . Zhu Jinlin, Ge Zhicliang, Song Zhihuan Chemometrics and Intelligent Laboratory Systems . 2015,第Null期

机译：多模式过程数据建模：一种基于Dirichlet过程混合物模型的贝叶斯鲁棒因子分析仪方法
2. A Computational Approach for Full Nonparametric Bayesian Inference Under Dirichlet Process Mixture Models [J] . Alan E. Geleand, Athanasios Kottas Journal of computational and graphical statistics: A joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America . 2002,第2期

机译：Dirichlet过程混合模型下全非参数贝叶斯推理的计算方法
3. Infinite Bayesian one-class support vector machine based on Dirichlet process mixture clustering [J] . Zhang Wei, Du Lan, Li Liling, Pattern Recognition: The Journal of the Pattern Recognition Society . 2018,第期

机译：无限贝叶斯一流的支持向量机基于Dirichlet Process混合体聚类
4. Dirichlet-process-mixture-based Bayesian nonparametric method for Markov switching process estimation [C] . Magnant Clement, Giremus Audrey, Grivel Eric, European Signal Processing Conference . 2015

机译：基于狄利克雷过程混合的贝叶斯非参数马尔可夫切换过程估计
5. Using Dirichlet process priors for Bayesian mixture clustering [D] . Huang, Xiao 2011

机译：使用Dirichlet过程先验进行贝叶斯混合聚类
6. Identifying latent subgroups of children with developmental delay using Bayesian sequential updating and Dirichlet process mixture modelling [O] . Patricia Gilholm, Kerrie Mengersen, Helen Thompson 2020

机译：使用贝叶斯顺序更新和Dirichlet过程混合建模识别发育迟缓儿童的潜在亚群
7. A computational approach for full nonparametric Bayesian inference under Dirichlet process mixture models [O] . Alan E. Gelfand, Athanasios Kottas 2002

机译：Dirichlet过程混合模型下完全非参数贝叶斯推断的一种计算方法

Efficient Bayesian approach to saliency detection based on Dirichlet process mixture

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