Computational cartoonist: A comic-style video summarization system for anime films

Tsukasa Fukusato*, Tatsunori Hirai, Shunya Kawamura, Shigeo Morishima

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)


This paper presents Computational Cartoonist, a comicstyle anime summarization system that detects key frame and generates comic layout automatically. In contract to previous studies, we define evaluation criteria based on the correspondence between anime films and original comics to determine whether the result of comic-style summarization is relevant. To detect key frame detection for anime films, the proposed system segments the input video into a series of basic temporal units, and computes frame importance using image characteristics such as motion. Subsequently, comic-style layouts are decided on the basis of pre-defined templates stored in a database. Several results demonstrate the efficiency of our key frame detection over previous methods by evaluating the matching accuracy between key frames and original comic panels.

Original languageEnglish
Title of host publicationMultiMedia Modeling - 22nd International Conference, MMM 2016, Proceedings
EditorsQi Tian, Richang Hong, Xueliang Liu, Nicu Sebe, Benoit Huet, Guo-Jun Qi
PublisherSpringer Verlag
Number of pages9
ISBN (Print)9783319276700
Publication statusPublished - 2016
Event22nd International Conference on MultiMedia Modeling, MMM 2016 - Miami, United States
Duration: 2016 Jan 42016 Jan 6

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other22nd International Conference on MultiMedia Modeling, MMM 2016
Country/TerritoryUnited States


  • Comic generation
  • Shot boundary detection
  • Shot clustering

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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