DOI QR코드

DOI QR Code

VR 및 AR 환경에서의 시공간 데이터 시각화를 위한 동향 분석

Spatio-temporal Data Visualization Survey for VR and AR Environment

  • 송현주 (덕성여자대학교 디지털미디어학과)
  • Song, Hyunjoo (Department of Digital Media, Duksung Women's University)
  • 투고 : 2017.11.13
  • 심사 : 2017.12.20
  • 발행 : 2018.01.30

초록

가상 현실(Virtual Reality) 및 증강 현실(Augmented Reality) 기기가 보급되면서 새로운 환경에서의 콘텐츠 제공 기술 연구에 대한 필요성이 증대되고 있다. 특히 해당 환경에서 제공할 수 있는 다양한 컨텐츠 중에서도 사물 인터넷(Internet of Things) 기기의 대중화로 인하여 다수의 일반 사용자들이 생산하고 활용하는 시공간 데이터가 증가하고 있다. 본 연구에서는 시공간 데이터에 대한 VR 및 AR 환경에서의 시각화를 위하여 먼저 데이터의 특성을 분석하였고, 일반 모니터를 사용하여 진행되었던 기존 연구에서의 시각화 기법들을 특성에 따라 분류하였다. 이를 통해 최신 기기의 사양 및 상호 작용 설계에 있어서의 특성을 반영하여, 기존 시각화 기법들의 차용 가능성을 살펴보았다. 본 연구의 결과를 통해 VR 및 AR 기기의 특성에 맞춰 시공간 데이터 시각화를 설계할 수 있을 것으로 기대된다.

VR(Virtual Reality) and AR(Augmented Reality) devices are becoming more common, and the need for proper contents presentation techniques in such environments has been growing ever since the popularization of the devices. One of the contents is the spatio-temporal data, which has become more prominent since it could be both generated and consumed by a large number of ordinary users. In this work, the researcher analyzed the characteristics of spatio-temporal data as a source for visualization in VR and AR environment, and categorized prior visualization methods for such data, which were devised for traditional monitors. The researcher also reviewed the hardware specification of state-of-the-art devices, and examined the possibility of adopting the previous visualization approaches. This work is expected to contribute in designing spatio-temporal visualization for VR and AR environment by utilizing their unique characteristics.

키워드

참고문헌

  1. E. Olshannikova, A. Ometov, Y. Koucheryavy, and T. Olsson, "Visualizing big data with augmented and virtual reality: challenges and research agenda," Journal of Big Data, Vol. 2, No. 1, pp.22, October 2015. https://doi.org/10.1186/s40537-015-0031-2
  2. I. Kim, C. Eem, and H. Hong, "Hierarchical subdivision of light distribution model for realistic shadow generation in augmented reality," Journal of Broadcast Engineering, Vol. 21, No. 1, pp.24-35, January 2016. https://doi.org/10.5909/JBE.2016.21.1.24
  3. K.-H. Yoo, "Standard model for live actor and entity representation in mixed and augmented reality," Journal of Broadcast Engineering, Vol. 21, No. 2, pp.192-199, March 2016. https://doi.org/10.5909/JBE.2016.21.2.192
  4. E. Kim, J. Kim, E. Yoo, and T. Park, "Study on virtual reality (VR) operating system prototype," Journal of Broadcast Engineering, Vol. 22, No. 1, pp.87-94, January 2017. https://doi.org/10.5909/JBE.2017.22.1.87
  5. Quantified self, http://quantifiedself.com (accessed Nov. 10, 2017).
  6. G. Sun, Y. Liu, W. Wu, R. Liang, and H. Qu, "Embedding temporal display into maps for occlusion-free visualization of spatio-temporal data," Proceedings of IEEE Pacific Visualization Symposium, Yokohama, Japan, March 2014.
  7. E. R. Tufte, "Envisioning information," Optometry and Vision Science, Vol. 68, No. 4, pp.322-324, April 1991.
  8. N. Andrienko and G. Andrienko, "Interactive visual tools to explore spatio-temporal variation," Proceedings of the working conference on Advanced Visual Interfaces, Gallipoli, Italy, pp.417-420, 2004.
  9. Map of Seoul, https://commons.wikimedia.org/wiki/File:Image-Map_Seoul-teukbyeolsi-big.png (accessed Nov. 10, 2017).
  10. N. Andrienko and G. Andrienko, "Visual data exploration using space-time cube," Proceedings of International Cartographic Conference, Durban, South Africa, pp.1981-1983, 2003.
  11. A. M. MacEachren, How Maps Work: Representation, Visualization, and Design, The Guilford Press, New York, USA, pp.252-254, 1995.
  12. B. Bach, P. Dragicevic, D. Archambault, C. Hurter, and S. Carpendale, "A review of temporal data visualizations based on space-time cube operations," Eurographics Conference on Visualization, Swansea, Wales, United Kingdom, 2014.
  13. E. R. Tufte, The visual display of quantitative information, Graphics Press, Cheshire, USA, 1986.
  14. P. Gatalsky, N. Andrienko, and G. Andrienko, "Interactive analysis of event data using space-time cube," Proceedings of the Information Visualization, Washington DC, USA, pp.145-152, 2004.
  15. K. Kurzhals, F. Heimerl, and D. Weiskopf, "ISeeCube: visual analysis of gaze data for video," Proceedings of the Symposium on Eye Tracking Research and Applications, Safety Harbor, Florida, USA, pp.43-50, 2014.
  16. D. A. Keim, "Information visualization and visual data mining," IEEE Transactions on Visualization and Computer Graphics, Vol. 8, No. 1, pp.1-8, January 2002. https://doi.org/10.1109/2945.981847
  17. C. Cruz-Neira, D. J. Sandin, T. A. DeFanti, R. V. Kenyon, and J. C. Hart, "The CAVE: audio visual experience automatic virtual environment," Communications of the ACM, Vol. 35, No. 6, pp.64-72, June 1992.
  18. J. S. Yi, Y. Kang, and J. T. Stasko, "Toward a deeper understanding of the role of interaction in information visualization," IEEE Transactions on Visualization and Computer Graphics, Vol. 13, No. 6, pp.1224-1231 November 2007. https://doi.org/10.1109/TVCG.2007.70515
  19. E. M. Kolasinski, Simulator sickness in virtual environments, U.S. Army Research Institute for the Behavioral and Social Sciences, Alexandria, USA, 1995.
  20. O. Kwon, C. Muelder, K. Lee, and K.-L. Ma, "A study of layout, rendering, and interaction methods for immersive graph visualization," IEEE Transactions on Visualization and Computer Graphics, Vol. 22, No. 7, pp.1802-1815, July 2016. https://doi.org/10.1109/TVCG.2016.2520921
  21. F. Barahimi, and S. Wismath, "3D graph visualization with the oculus rift," Proceedings of International Symposium on Graph Drawing, Wurzburg, Germany, pp.519-520, 2014.
  22. Q. Lin,Z. Xu, B. Li, R. Baucom, B. Poulose, B. A. Landman, and R. E. Bodenheimer, "Immersive virtual reality for visualization of abdominal CT," Proceedings of SPIE, 8673, 2013, http://doi.org/10.1117/12.2008050 (accessed Nov. 10, 2017).
  23. Yelp, https://www.yelp.com (accessed Nov. 10, 2017).