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VideoSense: a contextual video advertising system

Published: 29 September 2007 Publication History

Abstract

This demonstration presents a novel contextual advertising platform for online video service, called VideoSense. Unlike most current video-oriented sites that only display a video ad at the beginning or the end of a video, VideoSense aims to embed more contextually relevant ads at less intrusive positions within the video stream. Given an online video, VideoSense is able to detect a set of candidate ad insertion points based on content analysis, select a list of relevant candidate ads ranked according to textual relevance, and find the best match between insertion points and ads which maximizes the overall multimodal relevance. The effectiveness of VideoSense supporting contextually relevant and less intrusive advertising is validated by the user studies conducted on a variety of online video documents.

References

[1]
Google Video. http://video.google.com/.
[2]
X.-S. Hua, L. Lu, and H.-J. Zhang. Optimization-based automated home video editing system. IEEE Trans. on Circuit and Syst. for Video Tech., 14(5):572--583, 2004.
[3]
Revver. http://one.revver.com/revver.
[4]
B. Yang, T. Mei, X.-S. Hua, L. Yang, S.-Q. Yang, and M. Li. Online video recommendation based on multimodal fusion and relevance feedback. In Proceedings of ACM International Conference on Image and Video Retrieval, July 2007.
[5]
YouTube. http://www.youtube.com/.

Cited By

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  • (2025)Explainable Video Topics for Content Taxonomy: A Multimodal Retrieval Approach to Industry-Compliant Contextual AdvertisingIEEE Access10.1109/ACCESS.2025.354256213(30597-30612)Online publication date: 2025
  • (2018)PageSenseIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2016.259870228:1(254-266)Online publication date: 1-Jan-2018
  • (2014)On the Influence Propagation of Web VideosIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2013.14226:8(1961-1973)Online publication date: Aug-2014
  • Show More Cited By

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Published In

cover image ACM Conferences
MM '07: Proceedings of the 15th ACM international conference on Multimedia
September 2007
1115 pages
ISBN:9781595937025
DOI:10.1145/1291233
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 September 2007

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Author Tags

  1. ad insertion point detection
  2. online video advertising

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MM07

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

View all
  • (2025)Explainable Video Topics for Content Taxonomy: A Multimodal Retrieval Approach to Industry-Compliant Contextual AdvertisingIEEE Access10.1109/ACCESS.2025.354256213(30597-30612)Online publication date: 2025
  • (2018)PageSenseIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2016.259870228:1(254-266)Online publication date: 1-Jan-2018
  • (2014)On the Influence Propagation of Web VideosIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2013.14226:8(1961-1973)Online publication date: Aug-2014
  • (2009)Characterizing use and quality of textual attributes in Web 2.0 applicationsProceedings of the XV Brazilian Symposium on Multimedia and the Web10.1145/1858477.1858486(1-8)Online publication date: 5-Oct-2009

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