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Frontiers of Computer Science

ISSN 2095-2228

ISSN 2095-2236(Online)

CN 10-1014/TP

邮发代号 80-970

2019 Impact Factor: 1.275

Frontiers of Computer Science  2015, Vol. 9 Issue (5): 691-702   https://doi.org/10.1007/s11704-015-4237-4
  本期目录
Camera array calibration for light field acquisition
Yichao XU(),Kazuki MAENO,Hajime NAGAHARA,Rin-ichiro TANIGUCHI
Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan
 全文: PDF(927 KB)  
Abstract

Light field cameras are becoming popular in computer vision and graphics, with many research and commercial applications already having been proposed.Various types of cameras have been developed with the camera array being one of the ways of acquiring a 4D light field image usingmultiple cameras. Camera calibration is essential, since each application requires the correct projection and ray geometry of the light field. The calibrated parameters are used in the light field image rectified from the images captured by multiple cameras. Various camera calibration approaches have been proposed for a single camera, multiple cameras, and amoving camera. However, although these approaches can be applied to calibrating camera arrays, they are not effective in terms of accuracy and computational cost. Moreover, less attention has been paid to camera calibration of a light field camera. In this paper, we propose a calibration method for a camera array and a rectification method for generating a light field image from the captured images. We propose a two-step algorithm consisting of closed form initialization and nonlinear refinement, which extends Zhang’swell-known method to the camera array. More importantly, we introduce a rigid camera constraint whereby the array of cameras is rigidly aligned in the camera array and utilize this constraint in our calibration. Using this constraint, we obtained much faster and more accurate calibration results in the experiments.

Key wordslight field    camera array    calibration    rectification    digital refocusing
收稿日期: 2014-05-15      出版日期: 2015-09-24
Corresponding Author(s): Yichao XU   
 引用本文:   
. [J]. Frontiers of Computer Science, 2015, 9(5): 691-702.
Yichao XU,Kazuki MAENO,Hajime NAGAHARA,Rin-ichiro TANIGUCHI. Camera array calibration for light field acquisition. Front. Comput. Sci., 2015, 9(5): 691-702.
 链接本文:  
https://academic.hep.com.cn/fcs/CN/10.1007/s11704-015-4237-4
https://academic.hep.com.cn/fcs/CN/Y2015/V9/I5/691
1 Levoy M, Hanrahan P. Light field rendering. In: Proceedings of the ACM Conference on Computer Graphics. 1996, 31―42
https://doi.org/10.1145/237170.237199
2 Ng R, Levoy M, Brédif M, Duval G, Horowitz M, Hanrahan P. Light Field Photography with a Hand-Held Plenoptic Camera. Computer Science Technical Report CSTR, 2005
3 Vaish V, Levoy M, Szeliski R, Zitnick C L, Kang S B. Reconstructing occluded surfaces using synthetic apertures: stereo, focus and robust measures. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2006, 2331―2338
https://doi.org/10.1109/cvpr.2006.244
4 Seitz S M, Curless B, Diebel J, Scharstein D, Szeliski R S. A comparison and evaluation of multi-view stereo reconstruction algorithms. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2006, 519―528
https://doi.org/10.1109/cvpr.2006.19
5 Wetzstein G, Roodnick D, Heidrich W, Raskar R. Refractive shape from light field distortion. In: Proceedings of IEEE International Conference on Computer Vision. 2011, 1180―1186
https://doi.org/10.1109/iccv.2011.6126367
6 Maeno K, Nagahara H, Shimada A, Taniguchi R. Light field distortion feature for transparent object recognition. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2013, 2786―2793
https://doi.org/10.1109/cvpr.2013.359
7 Wilburn B, Joshi N, Vaish V, Talvala E V E, Antunez E, Barth A, Adams A, Levoy M, Horowitz M. High performance imaging using large camera arrays. ACM Transactions on Graphics, 2005, 24(3): 765―776
https://doi.org/10.1145/1073204.1073259
8 Zhang Z. A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(11): 1330―1334
https://doi.org/10.1109/34.888718
9 Ueshiba T, Tomita F. Plane-based calibration algorithm for multicamera systems via factorization of homography matrices. In: Proceedings of IEEE International Conference on Computer Vision. 2003, 966―973
https://doi.org/10.1109/ICCV.2003.1238453
10 Snavely N, Seitz S M, Szeliski R. Modeling the world from internet photo collections. International Journal of Computer Vision, 2008, 80: 189―210
https://doi.org/10.1007/s11263-007-0107-3
11 Bok Y, Jeon H G, Kweon I S. Geometric calibration of micro-lensbased light-field cameras using line features. In: Proceedings of European Conference on Computer Vision. 2014, 8694: 47―61
12 Dansereau D G, Pizarro O, Williams S B. Decoding, calibration and rectification for lenselet-based plenoptic cameras. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2013, 1027―1034
https://doi.org/10.1109/cvpr.2013.137
13 Cho D, Lee M, Kim S, Tai Y W. Modeling the calibration pipeline of the lytro camera for high quality light-field image reconstruction. In: Proceedings of IEEE International Conference on Computer Vision. 2013
https://doi.org/10.1109/iccv.2013.407
14 Tsai R Y. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE Journal of Robotics and Automation, 1987, 3: 323―344
https://doi.org/10.1109/JRA.1987.1087109
15 Vaish V, Wilburn B, Joshi N, Levoy M. Using plane+ parallax for calibrating dense camera arrays. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (1). 2004, 2―9
https://doi.org/10.1109/cvpr.2004.1315006
16 Svoboda T, Martinec D, Pajdla T. A convenient multi-camera selfcalibration for virtual environments. PRESENCE: Teleoperators and Virtual Environments, 2005, 14(4): 407―422
https://doi.org/10.1162/105474605774785325
17 Loop C, Zhang Z. Computing rectifying homographies for stereo vision. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 1999, 125―131
https://doi.org/10.1109/cvpr.1999.786928
18 Fusiello A, Trucco E, Verri A. A compact algorithm for rectification of stereo pairs. Machine Vision and Applications, 2000, 12(1): 16―22
https://doi.org/10.1007/s001380050120
19 Deng K, Wang L, Lin Z, Feng T, Deng Z. Correction and rectification of light fields. Computers & Graphics, 2003, 27(2): 169―177
https://doi.org/10.1016/S0097-8493(02)00274-1
20 Fukushima N, Yendo T, Fujii T, Tanimoto M. A novel rectification method for two-dimensional camera array by parallelizing locus of feature points. In: Proceedings of International Workshop on Advanced Image Technology. 2008, B5―1
21 Heikkila J, Silven O. A four-step camera calibration procedure with implicit image correction. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 1997, 1106―1112
https://doi.org/10.1109/CVPR.1997.609468
22 Wei G Q, Ma S D. Implicit and explicit camera calibration: Theory and experiments. IEEE Transactions of Pattern Analysis and Machine Intelligence, 1994, 16(5): 469―480
https://doi.org/10.1109/34.291450
23 Levenberg K. A method for the solution of certain non-linear problems in least squares. Quarterly Journal of Applied Mathmatics, 1944, II(2): 164―168
24 Marquardt D W. An algorithm for least-squares estimation of nonlinear parameters. SIAM Journal on Applied Mathematics, 1963, 11(2): 431―441
https://doi.org/10.1137/0111030
25 Ihm I, Park S, Lee R K. Rendering of spherical light fields. In: Proceedings of the 5th Pacific Conference On Computer Graphics And Applications. 1997, 59―68
26 Georgiev T, Lumsdaine A. Focused plenoptic camera and rendering. Journal of Electronic Imaging, 2010, 19(2)
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