ETRI Journal

  • 제45권2호
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  • Pages.291-303
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  • 2023
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  • 1225-6463(pISSN)
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  • 2233-7326(eISSN)
한국전자통신연구원 (Electronics and Telecommunications Research Institute)
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Virtual portraits from rotating selfies

  • Yongsik Lee (Telecommunications & Media Research, Electronics and Telecommunications Research Institute) ;
  • Jinhyuk Jang (Artificial Intelligence Research, Electronics and Telecommunications Research Institute) ;
  • SeungjoonYang (Department of Electrical Engineering, Ulsan National Institute of Science and Technology)
  • 투고 : 2021.11.10
  • 심사 : 2022.05.23
  • 발행 : 2023.04.20
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초록

Selfies are a popular form of photography. However, due to physical constraints, the compositions of selfies are limited. We present algorithms for creating virtual portraits with interesting compositions from a set of selfies. The selfies are taken at the same location while the user spins around. The scene is analyzed using multiple selfies to determine the locations of the camera, subject, and background. Then, a view from a virtual camera is synthesized. We present two use cases. After rearranging the distances between the camera, subject, and background, we render a virtual view from a camera with a longer focal length. Following that, changes in perspective and lens characteristics caused by new compositions and focal lengths are simulated. Second, a virtual panoramic view with a larger field of view is rendered, with the user's image placed in a preferred location. In our experiments, virtual portraits with a wide range of focal lengths were obtained using a device equipped with a lens that has only one focal length. The rendered portraits included compositions that would be photographed with actual lenses. Our proposed algorithms can provide new use cases in which selfie compositions are not limited by a camera's focal length or distance from the camera.

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과제정보

This work was supported by the U-K BRAND Research Fund of Ulsan National Institute of Science & Technology (UNIST) (1.210040.01) (Contribution Rate: 34%). This work was supported by Institute for Information and Communications Technology Planning & Evaluation (IITP) grant funded by the Korean government (MSIP) (No. 2018-0-00198, Contribution Rate: 33%). This research was supported by 2022 Cultural Heritage Smart Preservation & Utilization R&D Program of Cultural Heritage Administration, National Research Institute of Cultural Heritage (Project Name: Development of AI based CAD conversion technology for traditional architecture drawing images, Project Number: 2022A02P03-001, Contribution Rate: 33%).

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