DOI QR코드

DOI QR Code

DOF Correction of Heterogeneous Stereoscopic Cameras

이종 입체영상 카메라의 피사계심도 일치화

  • Choi, Sung-In (School of Computer Science and Engineering, Kyungpook National University) ;
  • Park, Soon-Yong (School of Computer Science and Engineering, Kyungpook National University)
  • 최성인 (경북대학교 IT대학 컴퓨터학부) ;
  • 박순용 (경북대학교 IT대학 컴퓨터학부)
  • Received : 2014.02.25
  • Accepted : 2014.06.27
  • Published : 2014.07.25

Abstract

In this paper, we propose a DOF (Depth of Field) correction technique by determining the values of the internal parameters of a 3-D camera which consists of stereoscopic cameras of different optical properties. If there is any difference in the size or the depth range of focused objects in the left and right stereoscopic images, it could cause visual fatigue to human viewers. The object size of in the stereoscopic image is corrected by the LUT of zoom lenses, and the forward and backward DOF are corrected by the object distance. Then the F-numbers are determined to adjust the optical properties of the camera for DOF correction. By applying the proposed technique to a main-sub type 3-D camera using a GUI-based DOF simulator, the DOF of the camera is automatically corrected.

본 논문에서는 서로 다른 광학적 특성을 가지는 3차원 카메라의 내부 변수 값을 자동으로 결정하여 스테레오 영상의 심도를 일치시키는 기술을 제안한다. 3차원 카메라에서 획득한 스테레오 영상에서 물체의 크기가 다르거나 심도의 차이가 큰 경우에 사람의 눈은 시각적 피로감을 느끼게 된다. 획득된 좌, 우 영상에서 물체의 크기가 동일하도록 카메라의 줌(zoom)을 LUT(Look Up Table)을 이용하여 일치시키고 피사체까지의 거리에 따라 전방심도와 후방심도의 범위를 결정한다. 이들을 이용하여 렌즈의 F-값을 결정하고 카메라의 광학 특성값을 자동으로 조절함으로써 스테레오 영상의 심도를 일치시킨다. 주-부 방식의 3차원 카메라와 GUI 소프트웨어를 통한 실험을 통하여 제안한 방법으로 스테레오 영상의 심도를 자동으로 일치시킬 수 있음을 보였다.

Keywords

References

  1. H. C. Lee, "3D video and human factor," The institute of Electronics Engineers of Korea, vol. 37, No. 9, pp. 960-968, Sept. 2010.
  2. 3Ality, http://3alitydigital.com/
  3. Sony, http://pro.sony.com/
  4. J. Knight, I. Reid, "Active visual alignment of a mobile stereo camera platform," in Proceedings of IEEE Conference on Robotics and Automation (ICRA), San Francisco, USA, April 2000.
  5. P. Surman, I. Sexton, K. Hopf, W. K. Lee, E. Buckley, G. Jones, and R. Bates, "European Research into Head Tracked Autostereoscopic Displays," 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video, Istanbul, May 2008.
  6. C. Doutre, M. T. Pourazad, A. Tourapis, P. Nasiopoulos and R. K. Ward, "Correcting Unsynchronized Zoom in 3D Video," in Proceedings of IEEE Symposium on Circuits and Systems (ISCAS), Paris, France, June 2010.
  7. S. Kumar, C. Micheloni, C. Piciarelli, and G. L. Foresti, "Stereo rectification of uncalibrated and heterogeneous images," Pattern Recognition Letters, vol. 31, No. 11, pp.1445-1452, 2010. https://doi.org/10.1016/j.patrec.2010.03.019
  8. R. Hartley, and A. Zisserman, Multiple View Geometry in Computer Vision, 2nd ed., Cambridge Univ. press, pp. 202-207, 2004.
  9. E. K. Jung, S. H. Baek, S. Y. Park, and H. W. Jang, "Optical Properties Correction of a Heterogeneous Stereoscopic Camera," Journal of the Institute of Electronics Engineers of Korea, vol. 49, No. 11, pp. 74-85, 2012. https://doi.org/10.5573/ieek.2012.49.11.074
  10. E. Trucco and A. Verri, Introductory techniques for 3-D computer vision, Prentice hall, pp. 21, 1998.
  11. O. Grau, M. Muller, and J. Kluger, "Tools for 3D-TV Programme Production," 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video, Antalya, May 2011.
  12. H. Bay, T. Tuytelaars and L. V. Gool, "SURF: Speeded up robust features," In Proceeding of European Conference on Computer Vision (ECCV), Graz, May 2006.