Cluster Computing

, Volume 22, Supplement 4, pp 9661–9676 | Cite as

Multimedia and multi-feature cluster fusion model based on saliency for mobile network applications

  • Zhenze JiaEmail author
  • Xiaoguang Fan
  • Haoxiang Wang


This paper introduces the concept, advantages, structure, method and application of multisensor integration and data fusion, and lists four different integration characteristics of sensors. Data fusion technology combines data from different sensors or other information sources in order to improve the accuracy of location and feature estimation. In the process of data fusion, modeling includes signal model, noise model, converter model, data transformation model and fusion model. The data fusion model includes the fusion method and the structure. This paper introduces the integrated, distributed and hybrid fusion structures, and compares them. The visual saliency map to image processing technology depends on the quality of the obtained good results, the existing visual saliency detection method is usually only detected by visual saliency map attribute rough, seriously affected the image processing results. Therefore, a visual saliency detection method based on Bayesian theory and statistical learning is proposed to detect the visual saliency of the image. The method is based on Bayesian theory of the significance of static images. According to the bottom-up visual saliency model, the ROC curve was used for quantitative evaluation in the two standard data sets. The results show that the nonlinear combination effect is better than the linear combination.


Data fusion Models Visual saliency Multimedia Multiple features 


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© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.School of Aeronautics and Astronautics EngineeringAir Force Engineering UniversityXi’anChina
  2. 2.Department of ECECornell UniversityNew YorkUSA
  3. 3.R&D Center of GoPerception LaboratoryNew YorkUSA

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