Knowledge-driven understanding of images in comic books
Christophe Rigaud, Clément Guérin, Dimosthenis Karatzas, Jean-Christophe Burie, Jean-Marc Ogier
International Journal on Document Analysis and Recognition (IJDAR), 2015
Abstract
Document analysis is an active field of research, which can attain a complete understanding of the semantics of a given document. One example of the document understanding process is enabling a computer to identify the key elements of a comic book story and arrange them according to a predefined domain knowledge. In this study, we propose a knowledge-driven system that can interact with bottom-up and top-down information to progressively understand the content of a document. We model the comic book’s and the image processing domains knowledge for information consistency analysis. In addition, different image processing methods are improved or developed to extract panels, balloons, tails, texts, comic characters and their semantic relations in an unsupervised way.
Citation BibTeX
@article{
title={Knowledge-driven understanding of images in comic books},
author={Rigaud, Christophe and Gu{'e}rin, Cl{'e}ment and Karatzas, Dimosthenis and Burie, Jean-Christophe and Ogier, Jean-Marc},
issn={1433-2833},
journal={International Journal on Document Analysis and Recognition (IJDAR)},
doi={10.1007/s10032-015-0243-1},
url={http://dx.doi.org/10.1007/s10032-015-0243-1},
publisher={Springer Berlin Heidelberg},
pages={1-23},
year={2015}
}