Effective Comic-Like Representations with Embedded Regions of Interest

  • Luis Herranz
  • Huiying Liu
  • Shuqiang Jiang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7674)


Comic-like summaries exploit the narrative structure of comics to create intuitive and easily readable abstracts. However, real comics use complex composition techniques which are difficult to mimic in an unsupervised way as they involve high level semantic understanding. This paper explores the use of visual attention analysis and face detection to embed regions of interest in adjacent images, obtaining more compact yet informative representations. This paper also addresses the generation of the layout, which involves combinatorial optimization problems. In practice, using exhaustive search to solve the problem is not feasible due to the large number of images. A split and merge approach is proposed to effectively address the layout problem, thus the limitations of finding solutions in a wide range of row widths can be avoided. A user study conducted on several episodes of TV series confirmed the utility of the proposed approach.


Comics layout visual attention video summarizations regions of interest 


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  1. 1.
    Calic, J., Campbell, N.W.: Compact visualisation of video summaries. EURASIP Journal on Advances in Signal Processing 2007(2), 14 pages (2007)Google Scholar
  2. 2.
    Calic, J., Gibson, D.P., Campbell, N.W.: Efficient layout of comic-like video summaries. IEEE Transactions on Circuits and Systems for Video Technology 17(7), 931–936 (2007)CrossRefGoogle Scholar
  3. 3.
    Frey, B.J., Dueck, D.: Clustering by passing messages between data points. Science 315, 972–976 (2007)MathSciNetzbMATHCrossRefGoogle Scholar
  4. 4.
    Girgensohn, A.: A fast layout algorithm for visual video summaries. In: Proc. of International Conference on Multimedia and Expo, vol. 2, pp. 77–80 (2003)Google Scholar
  5. 5.
    Hong, R., Yuan, X.-T., Xu, M., Wang, M., Yan, S., Chua, T.-S.: Movie2comics: a feast of multimedia artwork. In: Proceedings of the ACM International Conference on Multimedia, pp. 611–614 (2010)Google Scholar
  6. 6.
    Likert, R.: A technique for the measurement of attitudes. Archives of Psychology 22(140), 1–55 (1932)Google Scholar
  7. 7.
    Liu, H., Jiang, S., Huang, Q., Xu, C.: A generic virtual content insertion system based on visual attention analysis. In: Proc. of the ACM International Conference on Multimedia, pp. 379–388 (2008)Google Scholar
  8. 8.
    McCloud, S.: Understanding Comics: The Invisible Art. HarperCollins (May 1994)Google Scholar
  9. 9.
    Otsu, N.: A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man and Cybernetics 9(1), 62–66 (1979)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Uchihashi, S., Foote, J., Girgensohn, A., Boreczky, J.: Video manga: generating semantically meaningful video summaries. In: Proc. of the ACM International Conference on Multimedia, pp. 383–392 (1999)Google Scholar
  11. 11.
    Yeung, M.M., Yeo, B.-L.: Video visualization for compact presentation and fast browsing of pictorial content. IEEE Transactions on Circuits and Systems for Video Technology 7(5), 771–785 (1997)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Luis Herranz
    • 1
  • Huiying Liu
    • 1
  • Shuqiang Jiang
    • 1
  1. 1.Key Lab of Intelligent Information Processing, Institute of Computing TechnologyChinese Academy of SciencesBeijingChina

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