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Story-oriented Image Selection and Placement

MPS-Authors
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Nag Chowdhury,  Sreyasi
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Razniewski,  Simon
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Fulltext (public)

arXiv:1909.00692.pdf
(Preprint), 9MB

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Citation

Nag Chowdhury, S., Razniewski, S., & Weikum, G. (2019). Story-oriented Image Selection and Placement. Retrieved from http://arxiv.org/abs/1909.00692.


Cite as: http://hdl.handle.net/21.11116/0000-0005-83C9-4
Abstract
Multimodal contents have become commonplace on the Internet today, manifested as news articles, social media posts, and personal or business blog posts. Among the various kinds of media (images, videos, graphics, icons, audio) used in such multimodal stories, images are the most popular. The selection of images from a collection - either author's personal photo album, or web repositories - and their meticulous placement within a text, builds a succinct multimodal commentary for digital consumption. In this paper we present a system that automates the process of selecting relevant images for a story and placing them at contextual paragraphs within the story for a multimodal narration. We leverage automatic object recognition, user-provided tags, and commonsense knowledge, and use an unsupervised combinatorial optimization to solve the selection and placement problems seamlessly as a single unit.