Journal of the Korea Computer Graphics Society (한국컴퓨터그래픽스학회논문지)

Korea Computer Graphics Society (한국컴퓨터그래픽스학회)
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Improvement Depth Perception of Volume Rendering using Virtual Reality

가상현실을 통한 볼륨렌더링 깊이 인식 향상

  • Choi, JunYoung (Ulsan National Institute of Science and Technology (UNIST)) ;
  • Jeong, HaeJin (Ulsan National Institute of Science and Technology (UNIST)) ;
  • Jeong, Won-Ki (Ulsan National Institute of Science and Technology (UNIST))
  • Received : 2018.01.06
  • Accepted : 2018.05.10
  • Published : 2018.06.01
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Abstract

Direct volume rendering (DVR) is a commonly used method to visualize inner structures in 3D volumetric datasets. However, conventional volume rendering on a 2D display lacks depth perception due to dimensionality reduction caused by ray casting. In this work, we investigate how emerging Virtual Reality (VR) can improve the usability of direct volume rendering. We developed real-time high-resolution DVR system in virtual reality, and measures the usefulness of volume rendering with improved depth perception via a user study conducted by 38 participants. The result indicates that virtual reality significantly improves the usability of DVR by allowing better depth perception.

직접볼륨렌더링(DVR)은 3차원 볼륨 데이터의 내부 구조를 시각화하는 데 일반적으로 사용되는 방법이다. 그러나, 2차원 디스플레이 상의 기존의 볼륨 렌더링은 광선 투사법에 의한 차원 감소로 인해 깊이 인식이 부족하다. 본 연구에서는 가상현실이 볼륨렌더링의 유용성을 어떻게 향상시킬 수 있는지 조사한다. 우리는 가상 현실에서 실시간 고해상도 볼륨렌더링 시스템을 개발하고 38명의 참가자를 통한 사용자 연구를 통해 깊이 인식의 향상에 따른 볼륨렌더링의 유용성을 측정한다. 결과는 가상 현실이 뛰어난 깊이 인식을 가능하게 함으로써 볼륨렌더링의 유용성을 향상 시킨다는 것을 보여준다.

Keywords

Acknowledgement

Supported by : 한국연구재단, 한국과학창의재단

References

  1. M. Hadwiger, J. M. Kniss, C. Rezk-salama, D.Weiskopf, and K. Engel, Real-time Volume Graphics. Natick, MA, USA: A. K. Peters, Ltd., 2006.
  2. R. A. Drebin, L. Carpenter, and P. Hanrahan, "Volume rendering," in Proceedings of the 15th Annual Conference on Computer Graphics and Interactive Techniques, ser. SIGGRAPH '88. New York, NY, USA: ACM, 1988, pp. 65-74. [Online]. Available: http://doi.acm.org/10.1145/54852.378484
  3. S. J. Adelson and C. D. Hansen, "Fast stereoscopic images with ray-traced volume rendering," in Proceedings of the 1994 symposium on Volume visualization. ACM, 1994, pp. 3-9.
  4. C. Correa and K. L. Ma, "Size-based Transfer Functions: A New Volume Exploration Technique," IEEE Transactions on Visualization and Computer Graphics, vol. 14, no. 6, pp. 1380-1387, Nov. 2008. https://doi.org/10.1109/TVCG.2008.162
  5. L.-L. Cai, B. P. Nguyen, C.-K. Chui, and S.-H. Ong, "Rule-Enhanced Transfer Function Generation for Medical Volume Visualization," Computer Graphics Forum, vol. 34, no. 3, pp. 121-130, June 2015.
  6. P. Ljung, J. Kruger, E. Groller, M. Hadwiger, C. D. Hansen, and A. Ynnerman, "State of the art in transfer functions for direct volume rendering," in Computer Graphics Forum, vol. 35, no. 3. Wiley Online Library, 2016, pp. 669-691.
  7. T. M. Quan, J. Choi, H. Jeong, and W.-K. Jeong, "An intelligent system approach for probabilistic volume rendering using hierarchical 3d convolutional sparse coding," IEEE Transactions on Visualization and Computer Graphics, 2017.
  8. H. Guo, N. Mao, and X. Yuan, "Wysiwyg (what you see is what you get) volume visualization," IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 12, pp. 2106-2114, 2011. https://doi.org/10.1109/TVCG.2011.261
  9. K. P. Soundararajan and T. Schultz, "Learning Probabilistic Transfer Functions: A Comparative Study of Classifiers," Computer Graphics Forum, vol. 34, no. 3, pp. 111-120, June 2015.
  10. J. G. Magnus and S. Bruckner, "Interactive dynamic volume illumination with refraction and caustics," IEEE Transactions on Visualization and Computer Graphics, 2017.
  11. L. Zheng and K.-L. Ma, "Enhancing volume visualization with lightness anchoring theory," in Proceedings of the Computer Graphics International Conference. ACM, 2017, p. 20.
  12. M. Schott, A. Pascal Grosset, T. Martin, V. Pegoraro, S. T. Smith, and C. D. Hansen, "Depth of field effects for interactive direct volume rendering," in Computer Graphics Forum, vol. 30, no. 3. Wiley Online Library, 2011, pp. 941-950.
  13. A. P. Grosset, M. Schott, G.-P. Bonneau, and C. D. Hansen, "Evaluation of depth of field for depth perception in dvr," in Visualization Symposium (PacificVis), 2013 IEEE Pacific. IEEE, 2013, pp. 81-88.
  14. M. Mauderer, S. Conte, M. A. Nacenta, and D. Vishwanath, "Depth perception with gaze-contingent depth of field," in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ser. CHI '14. New York, NY, USA: ACM, 2014, pp. 217-226. [Online]. Available: http://doi.acm.org/10.1145/2556288.2557089
  15. M. Sousa, D. Mendes, S. Paulo, N. Matela, J. Jorge, and D. S. Lopes, "Vrrrroom: Virtual reality for radiologists in the reading room," in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 2017, pp. 4057-4062.
  16. A. Patney, M. Salvi, J. Kim, A. Kaplanyan, C. Wyman, N. Benty, D. Luebke, and A. Lefohn, "Towards foveated rendering for gaze-tracked virtual reality," ACM Trans. Graph., vol. 35, no. 6, pp. 179:1-179:12, Nov. 2016. [Online]. Available: http://doi.acm.org/10.1145/2980179.2980246
  17. J. Kruger and R. Westermann, "Acceleration techniques for gpu-based volume rendering," in Proceedings of the 14th IEEE Visualization 2003 (VIS'03). IEEE Computer Society, 2003, p. 38.
  18. B. T. Phong, "Illumination for computer generated pictures," Communications of the ACM, vol. 18, no. 6, pp. 311-317, 1975. https://doi.org/10.1145/360825.360839