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http://dx.doi.org/10.6109/jkiice.2020.24.11.1403

Generation of Stage Tour Contents with Deep Learning Style Transfer  

Kim, Dong-Min (Department of Computer Engineering, Kumoh National Institute of Technology)
Kim, Hyeon-Sik (Department of Computer Engineering, Kumoh National Institute of Technology)
Bong, Dae-Hyeon (Department of Computer Engineering, Kumoh National Institute of Technology)
Choi, Jong-Yun (Department of Computer Engineering, Kumoh National Institute of Technology)
Jeong, Jin-Woo (Department of Computer Engineering, Kumoh National Institute of Technology)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.24, no.11, 2020 , pp. 1403-1410 More about this Journal
Abstract
Recently, as interest in non-face-to-face experiences and services increases, the demand for web video contents that can be easily consumed using mobile devices such as smartphones or tablets is rapidly increasing. To cope with these requirements, in this paper we propose a technique to efficiently produce video contents that can provide experience of visiting famous places (i.e., stage tour) in animation or movies. To this end, an image dataset was established by collecting images of stage areas using Google Maps and Google Street View APIs. Afterwards, a deep learning-based style transfer method to apply the unique style of animation videos to the collected street view images and generate the video contents from the style-transferred images was presented. Finally, we showed that the proposed method could produce more interesting stage-tour video contents through various experiments.
Keywords
AI; Deep learning; Style transfer; Stage tour contents;
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