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A Multimodal High Level Video Segmentation for Content Targeted Online Advertising

  • Institut Polytechnique de Paris
  • University 'Politehnica' of Bucharest

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper we introduce a novel advertisement system, dedicated to multimedia documents broadcasted over the Internet. The proposed approach takes into account the consumer’s perspective and inserts contextual relevant ads at the level of the scenes boundaries, while reducing the degree of intrusiveness. From the methodological point of view, the major contribution of the paper concerns a temporal video segmentation method into scenes based on a multimodal (visual, audio and semantic) fusion of information. The experimental evaluation, carried out on a large dataset with more than 30 video documents validates the proposed methodology with average F1 scores superior to 85%.

Original languageEnglish
Title of host publicationAdvances in Visual Computing - 15th International Symposium, ISVC 2020, Proceedings
EditorsGeorge Bebis, Zhaozheng Yin, Edward Kim, Jan Bender, Kartic Subr, Bum Chul Kwon, Jian Zhao, Denis Kalkofen, George Baciu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages506-517
Number of pages12
ISBN (Print)9783030645588
DOIs
Publication statusPublished - 1 Jan 2020
Event15th International Symposium on Visual Computing, ISVC 2020 - San Diego, United States
Duration: 5 Oct 20207 Oct 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12510 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Symposium on Visual Computing, ISVC 2020
Country/TerritoryUnited States
CitySan Diego
Period5/10/207/10/20

Keywords

  • Advertisement insertion
  • Multimodal video analysis
  • Story detection
  • Temporal video segmentation

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