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AdOn: an intelligent overlay video advertising system

Published: 19 July 2009 Publication History

Abstract

This paper presents a new video advertising system, called AdOn, which supports intelligent overlay video ads. Unlike most current ad-networks such as Youtube that overlay the ads at fixed positions in the videos (e.g., on the bottom fifth of videos 15 seconds in), AdOn is able to automatically detect a set of spatio-temporal nonintrusive positions and associate the contextually relevant ads with these positions. The overlay positions are obtained on the basis of video structuring, face and text detection, as well as visual saliency analysis, so that the intrusiveness to the users can be minimized. The ads are selected according to content-based multimodal relevance so that advertising relevance can be maximized. AdOn represents one of the first attempts towards intelligent overlay video advertising by leveraging video content analysis techniques.

References

[1]
W.-S. Liao, K.-T. Chen, and W. H. Hsu. AdImage: Video advertising by image matching and ad scheduling optimization. In SIGIR, 2008.
[2]
H. Liu, S. Jiang, Q. Huang, and C. Xu. A generic virtual content insertion system based on visual attention analysis. In ACM Multimedia, 2008.
[3]
LiveRail. Q4 2008 state of the industry.
[4]
T. Mei, X.-S. Hua, L. Yang, and S. Li. Videosense: Towards effective online video advertising. In ACM Multimedia, 2007.
[5]
YouTube. http://www.youtube.com/.

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  • (2022)SmartShots: An Optimization Approach for Generating Videos with Data Visualizations EmbeddedACM Transactions on Interactive Intelligent Systems10.1145/348450612:1(1-21)Online publication date: 4-Mar-2022
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      cover image ACM Conferences
      SIGIR '09: Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
      July 2009
      896 pages
      ISBN:9781605584836
      DOI:10.1145/1571941

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 19 July 2009

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      Author Tags

      1. contextual relevance
      2. saliency detection
      3. video advertising

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      Overall Acceptance Rate 792 of 3,983 submissions, 20%

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      Cited By

      View all
      • (2024)Intelligent systems and consumer neuroscience in the age of computational advertisingManagement & Marketing10.2478/mmcks-2024-002019:3(441-470)Online publication date: 24-Oct-2024
      • (2023)L-Shape advertising for mobile video streaming services: Less intrusive while still effectiveDisplays10.1016/j.displa.2023.10243678(102436)Online publication date: Jul-2023
      • (2022)SmartShots: An Optimization Approach for Generating Videos with Data Visualizations EmbeddedACM Transactions on Interactive Intelligent Systems10.1145/348450612:1(1-21)Online publication date: 4-Mar-2022
      • (2020)Immersive media experience with MPEG OMAF multi-viewpoints and overlaysProceedings of the 11th ACM Multimedia Systems Conference10.1145/3339825.3393576(333-336)Online publication date: 27-May-2020
      • (2017)Towards Global Optimization in Display Advertising by Integrating Multimedia Metrics with Real-Time BiddingProceedings of the 25th ACM international conference on Multimedia10.1145/3123266.3123966(836-845)Online publication date: 23-Oct-2017
      • (2017)Optimizing Trade-offs Among Stakeholders in Real-Time Bidding by Incorporating Multimedia MetricsProceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3077136.3080802(205-214)Online publication date: 7-Aug-2017
      • (2016)Automated Coding of Political Video Ads for Political Science Research2016 IEEE International Symposium on Multimedia (ISM)10.1109/ISM.2016.0012(7-13)Online publication date: Dec-2016
      • (2014)Saliency-Based ApplicationsVisual Saliency Computation10.1007/978-3-319-05642-5_8(215-232)Online publication date: 2014
      • (2013)Mobile PointMe-based spatial haptic interaction with annotated media for learning purposesMultimedia Systems10.1007/s00530-012-0285-x19:2(131-149)Online publication date: 1-Mar-2013
      • (2013)From Increased Availability to Increased Productivity: How Researchers Benefit from Online ResourcesInformation Reuse and Integration in Academia and Industry10.1007/978-3-7091-1538-1_13(261-279)Online publication date: 22-Aug-2013
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