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Web Server based Hologram Image Production Pipeline System Implementation

웹 서버 기반의 홀로그램 영상 제작 파이프라인 시스템 구현

  • 김용정 (광운대학교 플라즈마바이오디스플레이학과) ;
  • 박찬수 (광운대학교 플라즈마바이오디스플레이학과) ;
  • 신석용 (광운대학교 플라즈마바이오디스플레이학과) ;
  • 김정호 (광운대학교 공간컴퓨팅센터) ;
  • 필리페 (광운대학교 공간컴퓨팅센터) ;
  • 이지윤 (광운대학교 실감융합콘텐츠학과) ;
  • 권순철 (광운대학교 스마트융합대학원) ;
  • 이승현 (광운대학교 인제니움학부)
  • Received : 2021.09.30
  • Accepted : 2021.10.18
  • Published : 2021.11.30

Abstract

In this paper, we proposed a pipeline system for holographic image production in a web server-based environment. There are time and spatial constraints for the existing holographic image production. The purpose of the proposed system is to obtain high-quality holographic images by reducing accessibility to users. It is a structure in which a video captured by a user in a web environment is transmitted to a server and converted into a frame for holographic image production through post-production. For high-quality holographic image acquisition, post-processing uses a deep learning-based algorithm. The proposed system provides various service tools in the web environment for user convenience. Through this method, the user's accessibility is improved when producing holographic images because images are taken in a web environment rather than in a limited space.

본 논문은 웹 서버 기반 환경에서 홀로그램 영상 제작을 위한 파이프라인 시스템을 제안하였다. 기존 홀로그램 영상 제작을 위해 시간 및 공간적인 제약이 존재한다. 제안하는 시스템을 통해 사용자에게 접근성을 높여 고품질의 홀로그램 영상을 획득하는 것을 목적으로 하였다. 웹 환경에서 사용자가 촬영한 동영상을 서버로 전송하여 후반 작업을 거쳐 홀로그램 영상 제작을 위한 프레임으로 변환하는 구조이다. 고품질 홀로그램 영상 획득을 위해 후반 작업은 딥러닝 기반의 알고리즘을 사용하였다. 제안하는 시스템은 사용자 편의를 위해 웹 환경에서 다양한 서비스 도구를 제공하였다. 이 방법을 통하여 제약된 공간이 아닌 웹 환경에서 영상을 촬영하기 때문에 홀로그램 영상 제작 시 사용자 접근성을 높였다.

Keywords

Acknowledgement

본 연구는 문화체육관광부 및 한국콘텐츠진흥원의 연구개발지원사업으로 수행되었음.(과제번호: R2021040083)

References

  1. J. Gu, "A Study on the 3D Contents Production Technology of Taepyungmu," International Journal of Advanced Culture Technology, vol. 5, no. 1, pp. 40-50, Mar. 2017. https://doi.org/10.17703/IJACT.2017.5.1.40
  2. Y. Gentet and M. K. Shevtsov, "Mobile holographic camera for recording color holograms," J. Opt. Technol., vol. 76, no. 7, pp. 399-401, 2009, doi: 10.1364/JOT.76.000399.
  3. Y. Gentet and P. Gentet, "CHIMERA, a new holoprinter technology combining low-power continuous lasers and fast printing," Appl. Opt., vol. 58, no. 34, pp. G226-G230, 2019, doi: 10.1364/AO.58.00G226.
  4. E. Courtwright, C. Yue and H. Wang, "Efficient resource management on template-based web servers," 2009 IEEE/IFIP International Conference on Dependable Systems & Networks, 2009, pp. 249-258, doi: 10.1109/DSN.2009.5270329.
  5. C. H. Kwon, "딥러닝 기반 한국어 실시간 TTS기술 비교," 문화기술의 융합, vol. 7, no. 1, pp. 640-645, Feb. 2021. https://doi.org/10.17703/JCCT.2021.7.1.640
  6. J.-W. Huh and S.-Y. Ohm, "비콘과 딥러닝 기술을 활용한 전자출입명부 자동등록시스템," 문화기술의 융합, vol. 6, no. 4, pp. 807-812, Nov. 2020. https://doi.org/10.17703/JCCT.2020.6.4.807
  7. P. Gentet, Y. Gentet and S. Lee, "Ultimate 04 the new reference for ultra-realistic color holography," 2017 International Conference on Emerging Trends & Innovation in ICT (ICEI), 2017, pp. 162-166, doi: 10.1109/ETIICT.2017.7977030.
  8. C. Song, R. Huo, S. Wang and C. Lv, "Transformer Equipment Temperature Monitoring Based on the Network Framework of Django," 2019 Chinese Automation Congress (CAC), 2019, pp. 4594-4597, doi: 10.1109/CAC48633.2019.8996768.
  9. S. Wen and W. Dang, "Research on Base64 Encoding Algorithm and PHP Implementation," 2018 26th International Conference on Geoinformatics, 2018, pp. 1-5, doi: 10.1109/GEOINFORMATICS.2018.8557068.
  10. Y. Wada, Y. Watanabe, K. Syoubu, J. Sawamoto and T. Katoh, "Virtual Database Technology for Distributed Database," 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops, 2010, pp. 214-219, doi: 10.1109/WAINA.2010.38.
  11. P. Li and X. Zhang, "The Design and Implementation of Web-based FTP Remote Management System," 2012 Second International Conference on Business Computing and Global Informatization, 2012, pp. 774-777, doi: 10.1109/BCGIN.2012.207.
  12. M. P. Anggadhita and Y. Widiastiwi, "Breaches Detection in Zebra Cross Traffic Light Using Haar Cascade Classifier," 2020 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS), 2020, pp. 272-277, doi: 10.1109/ICIMCIS51567.2020.9354275.
  13. A. Juhong and C. Pintavirooj, "Face recognition based on facial landmark detection," 2017 10th Biomedical Engineering International Conference (BMEiCON), 2017, pp. 1-4, doi: 10.1109/BMEiCON.2017.8229173.
  14. M. Tico and M. Vehvilainen, "Image Stabilization Based on Fusing the Visual Information in Differently Exposed Images," 2007 IEEE International Conference on Image Processing, 2007, pp. I - 117-I - 120, doi: 10.1109/ICIP.2007.4378905.
  15. Z. Wang and X. Yang, "Moving Target Detection and Tracking Based on Pyramid Lucas-Kanade Optical Flow," 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC), 2018, pp. 66-69, doi: 10.1109/ICIVC.2018.8492786.
  16. A. Borji, "What is a Salient Object? A Dataset and a Baseline Model for Salient Object Detection," in IEEE Transactions on Image Processing, vol. 24, no. 2, pp. 742-756, Feb. 2015, doi: 10.1109/TIP.2014.2383320.
  17. Q. Hou, M. Cheng, X. Hu, A. Borji, Z. Tu and P. H. S. Torr, "Deeply Supervised Salient Object Detection with Short Connections," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 4, pp. 815-828, 1 April 2019, doi: 10.1109/TPAMI.2018.2815688.
  18. K. He, X. Zhang, S. Ren, and J. Sun, "Deep Residual Learning for Image Recognition," in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2016, vol. 2016-Decem, pp. 770-778, doi: 10.1109/CVPR.2016.90.
  19. S. Zacharovas, A. Nikolskij, and J. Kuchin, "Mobile phone color holography," in Practical Holography XXIV: Materials and Applications, Feb. 2010, vol. 7619, p. 76190O, doi: 10.1117/12.837718.