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GameSense: game-like in-image advertising

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Abstract

Considering the continuously increasing availability and accessibility of multimedia contents via social networking sites, our research addresses how to monetize the social multimedia contents with an efficient advertising approach. This paper presents a novel game-like advertising system called GameSense, which is driven by the compelling contents of online images. The contextually relevant ads (i.e., product logos) are embedded at appropriate positions within the online games, which are created on the basis of online images. The ads are selected based on multimodal relevance, i.e. text relevance, user relevance and visual content similarity. The game is able to provide viewers rich experience and thus promotes the embedded ads to provide more effective advertising. GameSense represents one of the first attempts toward effective online mashup applications which connect a photo-sharing site with an advertising agency. The effectiveness of GameSense is evaluated over a large-scale real world image set.

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Acknowledgements

The authors would like to gratefully acknowledge Geoffry Nordlund, Xinmei Tian, Dong Liu , Jing Li and Bo Geng for their valuable comments and suggestions to this paper. The authors would also like to acknowledge Chris Liu, Wei Ma and Jinlian Guo for their contributions on developing the system. This research is supported by the National Key Basic Research Program of China (Grant No. 2005CB321901).

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Authors and Affiliations

  1. State Key Laboratory of Software Development Environment, Beihang University, Beijing, People’s Republic of China

    Lusong Li

  2. Microsoft Research Asia, Beijing, People’s Republic of China

    Tao Mei & Xian-Sheng Hua

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  1. Lusong Li
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  2. Tao Mei
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  3. Xian-Sheng Hua
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Corresponding author

Correspondence to Lusong Li.

Additional information

This work was performed when the first author visited Microsoft Research Asia as an intern.

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Li, L., Mei, T. & Hua, XS. GameSense: game-like in-image advertising. Multimed Tools Appl 49, 145–166 (2010). https://doi.org/10.1007/s11042-009-0399-0

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