DOI QR코드

DOI QR Code

Full-field Distortion Measurement of Virtual-reality Devices Using Camera Calibration and Probe Rotation

카메라 교정 및 측정부 회전을 이용한 가상현실 기기의 전역 왜곡 측정법

  • Yang, Dong-Geun (Space Optics Team, Advanced Instrumentation Institute, Korea Research Institute of Standards and Science) ;
  • Kang, Pilseong (Space Optics Team, Advanced Instrumentation Institute, Korea Research Institute of Standards and Science) ;
  • Ghim, Young-Sik (Space Optics Team, Advanced Instrumentation Institute, Korea Research Institute of Standards and Science)
  • 양동근 (한국표준과학연구원 첨단측정장비연구소 우주광학팀) ;
  • 강필성 (한국표준과학연구원 첨단측정장비연구소 우주광학팀) ;
  • 김영식 (한국표준과학연구원 첨단측정장비연구소 우주광학팀)
  • Received : 2019.10.31
  • Accepted : 2019.11.05
  • Published : 2019.12.25

Abstract

A compact virtual-reality (VR) device with wider field of view provides users with a more realistic experience and comfortable fit, but VR lens distortion is inevitable, and the amount of distortion must be measured for correction. In this paper, we propose two different full-field distortion-measurement methods, considering the characteristics of the VR device. The first is the distortion-measurement method using multiple images based on camera calibration, which is a well-known technique for the correction of camera-lens distortion. The other is the distortion-measurement method by measuring lens distortion at multiple measurement points by rotating a camera. Our proposed methods are verified by measuring the lens distortion of Google Cardboard, as a representative sample of a commercial VR device, and comparing our measurement results to a simulation using the nominal values.

가상현실 기기의 렌즈는 사용자의 편의성을 위한 적은 부피와 높은 현실감을 위한 넓은 시야각을 동시에 만족시켜야 하기 때문에 왜곡 수차가 필연적으로 발생하는데, 일반적인 렌즈보다 시야각이 넓고 왜곡 수차가 크기 때문에 측정이 어렵다. 본 논문에서는 가상현실 기기의 특성을 고려한 두 가지 왜곡 측정 방법을 제안하였다. 하나는 카메라 교정 방법 기반의 다중 이미지를 이용한 왜곡 측정법이며, 또 다른 하나는 카메라를 포함한 측정부를 직접 회전시켜 왜곡을 측정하는 다중 측정점을 이용한 왜곡 측정법이다. 제안된 방법들의 검증을 위해 시판된 가상현실 기기인 Google Cardboard 제품의 왜곡을 측정하고 설계 데이터를 통한 시뮬레이션 결과와 비교하였으며, 두 방법으로 측정된 왜곡 값은 시뮬레이션 결과와 비교했을 때 잘 부합하는 것으로 나타났다.

Keywords

References

  1. International Organization for Standardization, "Optics and photonics - Quality evaluation of optical systems - Determination of distortion," ISO 9039 (2008).
  2. International Organization for Standardization, "Photography - Digital cameras - Geometric distortion (GD) measurements," ISO 17850 (2015).
  3. J. Penczek, M. Hasan, B. S. Denning, R. Calpito, R. L. Austin, and P. A. Boynton, "31-2: Measuring interocular geometric distortion of near-eye displays," SID Symp. Dig. Tech. Pap. 50, 430-433 (2019).
  4. Z. Zhang, "A flexible new technique for camera calibration," IEEE Trans. Pattern Anal. Mach. Intell. 22, 1330-1334 (1999). https://doi.org/10.1109/34.888718
  5. L. Tan, Y. Wang, H. Yu, and J. Zhu, "Automatic camera calibration using active displays of a virtual pattern," Sensors 17, 685 (2017). https://doi.org/10.3390/s17040685
  6. S. B. Kang and R. Weiss, "Can we calibrate a camera using an image of a flat textureless Lamberian surface?," in Proc. Computer Vision - ECCV 2000 (Ireland, Dublin, June. 2000), pp. 640-654.
  7. Google, "Google Cardboard I/O 2015 Technical Specification," (Google Cardboard, 2015), https://arvr.google.com/cardboard/manufacturers (2018).