With the rapid proliferation of multimedia data in the internet, there has been a fast rise in the creation of videos for the viewers. This enables the viewers to skip the advertisement breaks in the videos, using ad blockers and ‘skip ad’ buttons – bringing online marketing and publicity to a stall. In this paper, we demonstrate a system that can effectively integrate a new advertisement into a video sequence. We use state-of-the-art techniques from deep learning and computational photogrammetry, for effective detection of existing adverts, and seamless integration of new adverts into video sequences. This is helpful for targeted advertisement, paving the path for next-gen publicity. Code related to this paper is available at: https://youtu.be/zaKpJZhBVL4.
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A. Nautiyal, K. McCabe, M. Hossari and S. Dev—Contributed equally and arranged alphabetically.
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In this paper, we interchangeably use both the terms, billboard and advert to indicate a candidate object for new advertisement integration in an image frame.
A demonstration video of our advert creation system can be accessed via https://youtu.be/zaKpJZhBVL4.
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The ADAPT Centre for Digital Content Technology is funded under the SFI Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund.
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Nautiyal, A. et al. (2019). An Advert Creation System for Next-Gen Publicity. In: , et al. Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2018. Lecture Notes in Computer Science(), vol 11053. Springer, Cham. https://doi.org/10.1007/978-3-030-10997-4_47
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Online ISBN: 978-3-030-10997-4
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