吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (4): 1237-1243.doi: 10.13229/j.cnki.jdxbgxb20170350

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Image annotation method based on Corr-LDA model

CAO Jie1, SU Zhe1, LI Xiao-xu1,2   

  1. 1.School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050,China;
    2.School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876,China
  • Received:2017-04-13 Online:2018-07-01 Published:2018-07-01

Abstract: Most of existing image annotation methods are based on the same topic space. In fact, categories are important information to determine the image annotation words, different classifications of images present different objects. In this paper, a new image annotation method based on Corr-LDA model is proposed. In this method all sorts of images are placed in different topic spaces, and the image annotation model suitable to each category is learned. Experiment results on Labelme and UIUC-Sport datasets show that the proposed method has better performance than other methods.

Key words: computer application, image annotation, probabilistic topic model, variational expectation maximization, Corr-LDA model

CLC Number: 

  • TP391
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