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JBE, vol. 23, no. 1, pp.53-62, January, 2018
Helper Classification via Three Dimensional Visualization of Character-net
Seung-Bo Park, Yoon Bae Jeon, Juhyun Park, and Eun Soon You
C.A E-mail: email@example.com
It is necessary to analyze the character that are a key element of the story in order to analyze the story. Current character analysis methods such as Character-net and RoleNet are not sufficient to classify the roles of supporting characters by only analyzing the results of the final accumulated stories. It is necessary to study the time series analysis method according to the story progress in order to analyze the role of supporting characters rather than the accumulated story analysis method. In this paper, we propose a method to classify helpers as a mentor and a best friend through 3-D visualization of Character-net and evaluate the accuracy of the method. WebGL is used to configure the interface for 3D visualization so that anyone can see the results on the web browser. It is also proposed that rules to distinguish mentors and best friends and evaluated their performance. The results of the evaluation of 10 characters selected for 7 films confirms that they are 90% accurate.
Keyword: Character-net, visualization, helper classification, mentor, best friend
 S.-B. Park, K.-J. Oh, and G.-S. Jo, “Social Network Analysis in a Movie using Character -net,” Multimedia Tools and Applications. vol. 59, no. 2, pp. 601-627, Jul. 2012.
 C. Y. Weng, W. T. Chu, and J. L. Wu, “RoleNet: movie analysis from the perspective of social network,” IEEE Transaction on Multimedia, vol. 11, no. 2. pp. 256-271, 2009.
 Y. Tsivian, “Cinemetrics, Part of the Humanities’ Cyberinfrastruc- ture,” Digital Tools in Media Studies: Analysis and Research: an Overview, Bielfeld: Transcript Verlag, pp. 93-100, 2009.
 C. E. Nothelfer, J. E. DeLong, and J. E. Cutting, “Shot Structure in Hollywood Film,” Indiana Undergraduate Journal of Cognitive Science, vol. 4, pp. 103-113, 2009.
 F. Brodbeck, Cinemetrics, http://cinemetrics. fredericbrodbeck.de
 Aristotele, Plato, Dionysius Longinus, Aristoteles’s Poetics, (translated by Cheon Myeong Hui), Moonyebooks, 2002.
 Y. Lim, (2016). “The Climax Expression Analysis Based on the Shot-list Data of Movies,” Journal of Broadcast Engineering, vol. 21, no. 6, pp. 965-976. Jul. 2016.
 J. Campbell, The Hero with A Thousand Faces, (translated by Lee Yoon Ki), Minumsa, 2004.
 C. Vogler, The Writer’s Journey, (translated by Ham Choon Sung), Bizandbiz, 2007.
 H. C. Kwan, Story Generation System in the Digital Storytelling : Focused on 'Story Engine Modelling, Korea National University of Arts, 2010.
 D. Marks, Inside Story: The Power of the Transformational Arc, Methuen Drama, 2006.
 V. L. Schmid, 45 Master Characters, (translated by Nam Gil Young), Badabooks, Oct. 2017.
 M. Kim, Z. Lee, and W. Kim, “Realtime Human Object Segmentation Using Image and Skeleton Characteristics,” Journal of Broadcast Engineering, vol. 21, no. 5, Sep. 2016.
 I.-K. Choia, H. Song, S. Lee, and J. Yoo, “Facial Expression Classification Using Deep Convolutional Neural Network,” Journal of Broadcast Engineering, vol. 22, No. 2, Mar. 2017.
 S.-B. Park, H. N. Kim, H. Kim, and G. S. Jo, “Exploiting Script- Subtitles Alignment to Scene Boundary Dectection in Movie,” 2010 IEEE International Symposium on Multimedia(ISM), pp. 49-56, Dec. 2010.