@inproceedings{dac5d85da6f74667a2c7ea5f82e27515,
title = "Computational cartoonist: A comic-style video summarization system for anime films",
abstract = "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.",
keywords = "Comic generation, Shot boundary detection, Shot clustering",
author = "Tsukasa Fukusato and Tatsunori Hirai and Shunya Kawamura and Shigeo Morishima",
note = "Funding Information: This research is supported in part by OngaCREST, CREST, JST.and by Research Fellowship for Young Scientists of Japan Society for the Promotion of Science (JSPS). Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 22nd International Conference on MultiMedia Modeling, MMM 2016 ; Conference date: 04-01-2016 Through 06-01-2016",
year = "2016",
doi = "10.1007/978-3-319-27671-7_4",
language = "English",
isbn = "9783319276700",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "42--50",
editor = "Qi Tian and Richang Hong and Xueliang Liu and Nicu Sebe and Benoit Huet and Guo-Jun Qi",
booktitle = "MultiMedia Modeling - 22nd International Conference, MMM 2016, Proceedings",
}