An Advert Creation System for 3D Product Placements

Ivan Bacher, Hossein Javidnia, Soumyabrata Dev, Rahul Agrahari, Murhaf Hossari, Matthew Nicholson, Clare Conran, Jian Tang, Peng Song, David Corrigan, François Pitié

ECML-PKDD 2020 pp. 224-239

doi:10.1007/978-3-030-67667-4_14 /ecmlpkdd/2020/bacher2020ecmlpkdd-advert/

Abstract

Over the past decade, the evolution of video-sharing platforms has attracted a significant amount of investments on contextual advertising. The common contextual advertising platforms utilize the information provided by users to integrate 2D visual ads into videos. The existing platforms face many technical challenges such as ad integration with respect to occluding objects and 3D ad placement. This paper presents a Video Advertisement Placement & Integration (Adverts) framework, which is capable of perceiving the 3D geometry of the scene and camera motion to blend 3D virtual objects in videos and create the illusion of reality. The proposed framework contains several modules such as monocular depth estimation, object segmentation, background-foreground separation, alpha matting and camera tracking. Our experiments conducted using Adverts framework indicates the significant potential of this system in contextual ad integration, and pushing the limits of advertising industry using mixed reality technologies.

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Cite

Text

Bacher et al. "An Advert Creation System for 3D Product Placements." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2020. doi:10.1007/978-3-030-67667-4_14

Markdown

[Bacher et al. "An Advert Creation System for 3D Product Placements." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2020.](https://mlanthology.org/ecmlpkdd/2020/bacher2020ecmlpkdd-advert/) doi:10.1007/978-3-030-67667-4_14

BibTeX

@inproceedings{bacher2020ecmlpkdd-advert,
  title     = {{An Advert Creation System for 3D Product Placements}},
  author    = {Bacher, Ivan and Javidnia, Hossein and Dev, Soumyabrata and Agrahari, Rahul and Hossari, Murhaf and Nicholson, Matthew and Conran, Clare and Tang, Jian and Song, Peng and Corrigan, David and Pitié, François},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  year      = {2020},
  pages     = {224-239},
  doi       = {10.1007/978-3-030-67667-4_14},
  url       = {https://mlanthology.org/ecmlpkdd/2020/bacher2020ecmlpkdd-advert/}
}